14,637 results on '"Hastie A"'
Search Results
2. Fitting Multilevel Factor Models
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Parshakova, Tetiana, Hastie, Trevor, and Boyd, Stephen
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Statistics - Machine Learning ,Computer Science - Machine Learning ,Computer Science - Mathematical Software ,Statistics - Computation ,62H12 ,G.4 - Abstract
We examine a special case of the multilevel factor model, with covariance given by multilevel low rank (MLR) matrix~\cite{parshakova2023factor}. We develop a novel, fast implementation of the expectation-maximization (EM) algorithm, tailored for multilevel factor models, to maximize the likelihood of the observed data. This method accommodates any hierarchical structure and maintains linear time and storage complexities per iteration. This is achieved through a new efficient technique for computing the inverse of the positive definite MLR matrix. We show that the inverse of an invertible PSD MLR matrix is also an MLR matrix with the same sparsity in factors, and we use the recursive Sherman-Morrison-Woodbury matrix identity to obtain the factors of the inverse. Additionally, we present an algorithm that computes the Cholesky factorization of an expanded matrix with linear time and space complexities, yielding the covariance matrix as its Schur complement. This paper is accompanied by an open-source package that implements the proposed methods.
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- 2024
3. Scalable recommender system based on factor analysis
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Ghandwani, Disha and Hastie, Trevor
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Statistics - Methodology ,Computer Science - Information Retrieval - Abstract
Recommender systems have become crucial in the modern digital landscape, where personalized content, products, and services are essential for enhancing user experience. This paper explores statistical models for recommender systems, focusing on crossed random effects models and factor analysis. We extend the crossed random effects model to include random slopes, enabling the capture of varying covariate effects among users and items. Additionally, we investigate the use of factor analysis in recommender systems, particularly for settings with incomplete data. The paper also discusses scalable solutions using the Expectation Maximization (EM) and variational EM algorithms for parameter estimation, highlighting the application of these models to predict user-item interactions effectively.
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- 2024
4. MMIL: A novel algorithm for disease associated cell type discovery
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Craig, Erin, Keyes, Timothy, Sarno, Jolanda, Zaslavsky, Maxim, Nolan, Garry, Davis, Kara, Hastie, Trevor, and Tibshirani, Robert
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Quantitative Biology - Quantitative Methods ,Computer Science - Machine Learning ,Statistics - Methodology - Abstract
Single-cell datasets often lack individual cell labels, making it challenging to identify cells associated with disease. To address this, we introduce Mixture Modeling for Multiple Instance Learning (MMIL), an expectation maximization method that enables the training and calibration of cell-level classifiers using patient-level labels. Our approach can be used to train e.g. lasso logistic regression models, gradient boosted trees, and neural networks. When applied to clinically-annotated, primary patient samples in Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL), our method accurately identifies cancer cells, generalizes across tissues and treatment timepoints, and selects biologically relevant features. In addition, MMIL is capable of incorporating cell labels into model training when they are known, providing a powerful framework for leveraging both labeled and unlabeled data simultaneously. Mixture Modeling for MIL offers a novel approach for cell classification, with significant potential to advance disease understanding and management, especially in scenarios with unknown gold-standard labels and high dimensionality., Comment: Erin Craig and Timothy Keyes contributed equally to this work
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- 2024
5. A Fast and Scalable Pathwise-Solver for Group Lasso and Elastic Net Penalized Regression via Block-Coordinate Descent
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Yang, James and Hastie, Trevor
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Statistics - Computation ,Computer Science - Machine Learning ,Computer Science - Mathematical Software ,Computer Science - Software Engineering - Abstract
We develop fast and scalable algorithms based on block-coordinate descent to solve the group lasso and the group elastic net for generalized linear models along a regularization path. Special attention is given when the loss is the usual least squares loss (Gaussian loss). We show that each block-coordinate update can be solved efficiently using Newton's method and further improved using an adaptive bisection method, solving these updates with a quadratic convergence rate. Our benchmarks show that our package adelie performs 3 to 10 times faster than the next fastest package on a wide array of both simulated and real datasets. Moreover, we demonstrate that our package is a competitive lasso solver as well, matching the performance of the popular lasso package glmnet.
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- 2024
6. Using Pre-training and Interaction Modeling for ancestry-specific disease prediction in UK Biobank
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Menestrel, Thomas Le, Craig, Erin, Tibshirani, Robert, Hastie, Trevor, and Rivas, Manuel
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Computer Science - Machine Learning ,Quantitative Biology - Quantitative Methods ,Statistics - Applications ,Statistics - Computation - Abstract
Recent genome-wide association studies (GWAS) have uncovered the genetic basis of complex traits, but show an under-representation of non-European descent individuals, underscoring a critical gap in genetic research. Here, we assess whether we can improve disease prediction across diverse ancestries using multiomic data. We evaluate the performance of Group-LASSO INTERaction-NET (glinternet) and pretrained lasso in disease prediction focusing on diverse ancestries in the UK Biobank. Models were trained on data from White British and other ancestries and validated across a cohort of over 96,000 individuals for 8 diseases. Out of 96 models trained, we report 16 with statistically significant incremental predictive performance in terms of ROC-AUC scores (p-value < 0.05), found for diabetes, arthritis, gall stones, cystitis, asthma and osteoarthritis. For the interaction and pretrained models that outperformed the baseline, the PRS score was the primary driver behind prediction. Our findings indicate that both interaction terms and pre-training can enhance prediction accuracy but for a limited set of diseases and moderate improvements in accuracy
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- 2024
7. The mosaic permutation test: an exact and nonparametric goodness-of-fit test for factor models
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Spector, Asher, Barber, Rina Foygel, Hastie, Trevor, Kahn, Ronald N., and Candès, Emmanuel
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Statistics - Methodology ,62H25 (Primary) 62G10, 62G09 (Secondary) - Abstract
Financial firms often rely on fundamental factor models to explain correlations among asset returns and manage risk. Yet after major events, e.g., COVID-19, analysts may reassess whether existing risk models continue to fit well: specifically, after accounting for a set of known factor exposures, are the residuals of the asset returns independent? With this motivation, we introduce the mosaic permutation test, a nonparametric goodness-of-fit test for preexisting factor models. Our method can leverage modern machine learning techniques to detect model violations while provably controlling the false positive rate, i.e., the probability of rejecting a well-fitting model, without making asymptotic approximations or parametric assumptions. This property helps prevent analysts from unnecessarily rebuilding accurate models, which can waste resources and increase risk. To illustrate our methodology, we apply the mosaic permutation test to the BlackRock Fundamental Equity Risk (BFRE) model. Although the BFRE model generally explains the most significant correlations among assets, we find evidence of unexplained correlations among certain real estate stocks, and we show that adding new factors improves model fit. We implement our methods in the python package mosaicperm., Comment: 42 pages, 13 figures
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- 2024
8. Enhanced Safety Surveillance of GSK’s Inactivated Quadrivalent Seasonal Influenza Vaccine in Belgium, Germany, and Spain During the 2022/2023 Influenza Season
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de la Cueva, Ignacio Salamanca, Gerber, Jennifer E., Hastie, Andrew, Brotons, Carlos, Panzer, Falko, Pirçon, Jean-Yves, Talsma, Paul, Eckermann, Tamara, Nikic, Vanja, Gomez, Xavier Martinez, and Alsdurf, Hannah
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- 2024
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9. Temporal dynamics of the multi-omic response to endurance exercise training
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Bae, Dam, Dasari, Surendra, Dennis, Courtney, Evans, Charles R, Gaul, David A, Ilkayeva, Olga, Ivanova, Anna A, Kachman, Maureen T, Keshishian, Hasmik, Lanza, Ian R, Lira, Ana C, Muehlbauer, Michael J, Nair, Venugopalan D, Piehowski, Paul D, Rooney, Jessica L, Smith, Kevin S, Stowe, Cynthia L, Zhao, Bingqing, Clark, Natalie M, Jimenez-Morales, David, Lindholm, Malene E, Many, Gina M, Sanford, James A, Smith, Gregory R, Vetr, Nikolai G, Zhang, Tiantian, Almagro Armenteros, Jose J, Avila-Pacheco, Julian, Bararpour, Nasim, Ge, Yongchao, Hou, Zhenxin, Marwaha, Shruti, Presby, David M, Natarajan Raja, Archana, Savage, Evan M, Steep, Alec, Sun, Yifei, Wu, Si, Zhen, Jimmy, Bodine, Sue C, Esser, Karyn A, Goodyear, Laurie J, Schenk, Simon, Montgomery, Stephen B, Fernández, Facundo M, Sealfon, Stuart C, Snyder, Michael P, Adkins, Joshua N, Ashley, Euan, Burant, Charles F, Carr, Steven A, Clish, Clary B, Cutter, Gary, Gerszten, Robert E, Kraus, William E, Li, Jun Z, Miller, Michael E, Nair, K Sreekumaran, Newgard, Christopher, Ortlund, Eric A, Qian, Wei-Jun, Tracy, Russell, Walsh, Martin J, Wheeler, Matthew T, Dalton, Karen P, Hastie, Trevor, Hershman, Steven G, Samdarshi, Mihir, Teng, Christopher, Tibshirani, Rob, Cornell, Elaine, Gagne, Nicole, May, Sandy, Bouverat, Brian, Leeuwenburgh, Christiaan, Lu, Ching-ju, Pahor, Marco, Hsu, Fang-Chi, Rushing, Scott, Walkup, Michael P, Nicklas, Barbara, Rejeski, W Jack, Williams, John P, Xia, Ashley, Albertson, Brent G, Barton, Elisabeth R, Booth, Frank W, Caputo, Tiziana, Cicha, Michael, De Sousa, Luis Gustavo Oliveira, Farrar, Roger, Hevener, Andrea L, Hirshman, Michael F, Jackson, Bailey E, Ke, Benjamin G, Kramer, Kyle S, Lessard, Sarah J, Makarewicz, Nathan S, Marshall, Andrea G, and Nigro, Pasquale
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Health Sciences ,Sports Science and Exercise ,Prevention ,Human Genome ,Cardiovascular ,Behavioral and Social Science ,Genetics ,Physical Activity ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,Generic health relevance ,Inflammatory and immune system ,Good Health and Well Being ,Animals ,Female ,Humans ,Male ,Rats ,Acetylation ,Blood ,Cardiovascular Diseases ,Databases ,Factual ,Endurance Training ,Epigenome ,Inflammatory Bowel Diseases ,Internet ,Lipidomics ,Metabolome ,Mitochondria ,Multiomics ,Non-alcoholic Fatty Liver Disease ,Organ Specificity ,Phosphorylation ,Physical Conditioning ,Animal ,Physical Endurance ,Proteome ,Proteomics ,Time Factors ,Transcriptome ,Ubiquitination ,Wounds and Injuries ,MoTrPAC Study Group ,Lead Analysts ,MoTrPAC Study Group ,General Science & Technology - Abstract
Regular exercise promotes whole-body health and prevents disease, but the underlying molecular mechanisms are incompletely understood1-3. Here, the Molecular Transducers of Physical Activity Consortium4 profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome and immunome in whole blood, plasma and 18 solid tissues in male and female Rattus norvegicus over eight weeks of endurance exercise training. The resulting data compendium encompasses 9,466 assays across 19 tissues, 25 molecular platforms and 4 training time points. Thousands of shared and tissue-specific molecular alterations were identified, with sex differences found in multiple tissues. Temporal multi-omic and multi-tissue analyses revealed expansive biological insights into the adaptive responses to endurance training, including widespread regulation of immune, metabolic, stress response and mitochondrial pathways. Many changes were relevant to human health, including non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health and tissue injury and recovery. The data and analyses presented in this study will serve as valuable resources for understanding and exploring the multi-tissue molecular effects of endurance training and are provided in a public repository ( https://motrpac-data.org/ ).
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- 2024
10. Navigating choices: a framework of consumer search
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Moore, Alexander K. and Hastie, Reid
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- 2024
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11. Immunological memory diversity in the human upper airway
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Ramirez, Sydney I., Faraji, Farhoud, Hills, L. Benjamin, Lopez, Paul G., Goodwin, Benjamin, Stacey, Hannah D., Sutton, Henry J., Hastie, Kathryn M., Saphire, Erica Ollmann, Kim, Hyun Jik, Mashoof, Sara, Yan, Carol H., DeConde, Adam S., Levi, Gina, and Crotty, Shane
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- 2024
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12. Factor Fitting, Rank Allocation, and Partitioning in Multilevel Low Rank Matrices
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Parshakova, Tetiana, Hastie, Trevor, Darve, Eric, and Boyd, Stephen
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Statistics - Machine Learning ,Computer Science - Machine Learning ,Computer Science - Mathematical Software ,Mathematics - Optimization and Control - Abstract
We consider multilevel low rank (MLR) matrices, defined as a row and column permutation of a sum of matrices, each one a block diagonal refinement of the previous one, with all blocks low rank given in factored form. MLR matrices extend low rank matrices but share many of their properties, such as the total storage required and complexity of matrix-vector multiplication. We address three problems that arise in fitting a given matrix by an MLR matrix in the Frobenius norm. The first problem is factor fitting, where we adjust the factors of the MLR matrix. The second is rank allocation, where we choose the ranks of the blocks in each level, subject to the total rank having a given value, which preserves the total storage needed for the MLR matrix. The final problem is to choose the hierarchical partition of rows and columns, along with the ranks and factors. This paper is accompanied by an open source package that implements the proposed methods.
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- 2023
13. A common polymorphism in the Intelectin-1 gene influences mucus plugging in severe asthma
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Everman, Jamie L, Sajuthi, Satria P, Liegeois, Maude A, Jackson, Nathan D, Collet, Erik H, Peters, Michael C, Chioccioli, Maurizio, Moore, Camille M, Patel, Bhavika B, Dyjack, Nathan, Powell, Roger, Rios, Cydney, Montgomery, Michael T, Eng, Celeste, Elhawary, Jennifer R, Mak, Angel CY, Hu, Donglei, Huntsman, Scott, Salazar, Sandra, Feriani, Luigi, Fairbanks-Mahnke, Ana, Zinnen, Gianna L, Michel, Cole R, Gomez, Joe, Zhang, Xing, Medina, Vivian, Chu, Hong Wei, Cicuta, Pietro, Gordon, Erin D, Zeitlin, Pamela, Ortega, Victor E, Reisdorph, Nichole, Dunican, Eleanor M, Tang, Monica, Elicker, Brett M, Henry, Travis S, Bleecker, Eugene R, Castro, Mario, Erzurum, Serpil C, Israel, Elliot, Levy, Bruce D, Mauger, David T, Meyers, Deborah A, Sumino, Kaharu, Gierada, David S, Hastie, Annette T, Moore, Wendy C, Denlinger, Loren C, Jarjour, Nizar N, Schiebler, Mark L, Wenzel, Sally E, Woodruff, Prescott G, Rodriguez-Santana, Jose, Pearson, Chad G, Burchard, Esteban G, Fahy, John V, and Seibold, Max A
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Biochemistry and Cell Biology ,Biomedical and Clinical Sciences ,Biological Sciences ,Asthma ,Lung ,Genetics ,Clinical Research ,2.1 Biological and endogenous factors ,Respiratory ,Child ,Humans ,Cytokines ,Epithelial Cells ,GPI-Linked Proteins ,Interleukin-13 ,Lectins ,Mucin 5AC ,Mucus ,Nasal Mucosa ,Polymorphism ,Genetic ,Respiratory Mucosa - Abstract
By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma.
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- 2024
14. Persistent mucus plugs in proximal airways are consequential for airflow limitation in asthma
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Huang, Brendan K, Elicker, Brett M, Henry, Travis S, Kallianos, Kimberly G, Hahn, Lewis D, Tang, Monica, Heng, Franklin, McCulloch, Charles E, Bhakta, Nirav R, Majumdar, Sharmila, Choi, Jiwoong, Denlinger, Loren C, Fain, Sean B, Hastie, Annette T, Hoffman, Eric A, Israel, Elliot, Jarjour, Nizar N, Levy, Bruce D, Mauger, Dave T, Sumino, Kaharu, Wenzel, Sally E, Castro, Mario, Woodruff, Prescott G, Fahy, John V, and Program, for the NHLBI Severe Asthma Research
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Biomedical and Clinical Sciences ,Clinical Sciences ,Lung ,Rare Diseases ,Asthma ,Respiratory ,Humans ,Bronchoscopy ,Mucus ,Tomography ,X-Ray Computed ,Clinical practice ,Diagnostic imaging ,Pulmonology ,Biomedical and clinical sciences ,Health sciences - Abstract
BACKGROUNDInformation about the size, airway location, and longitudinal behavior of mucus plugs in asthma is needed to understand their role in mechanisms of airflow obstruction and to rationally design muco-active treatments.METHODSCT lung scans from 57 patients with asthma were analyzed to quantify mucus plug size and airway location, and paired CT scans obtained 3 years apart were analyzed to determine plug behavior over time. Radiologist annotations of mucus plugs were incorporated in an image-processing pipeline to generate size and location information that was related to measures of airflow.RESULTSThe length distribution of 778 annotated mucus plugs was multimodal, and a 12 mm length defined short ("stubby", ≤12 mm) and long ("stringy", >12 mm) plug phenotypes. High mucus plug burden was disproportionately attributable to stringy mucus plugs. Mucus plugs localized predominantly to airway generations 6-9, and 47% of plugs in baseline scans persisted in the same airway for 3 years and fluctuated in length and volume. Mucus plugs in larger proximal generations had greater effects on spirometry measures than plugs in smaller distal generations, and a model of airflow that estimates the increased airway resistance attributable to plugs predicted a greater effect for proximal generations and more numerous mucus plugs.CONCLUSIONPersistent mucus plugs in proximal airway generations occur in asthma and demonstrate a stochastic process of formation and resolution over time. Proximal airway mucus plugs are consequential for airflow and are in locations amenable to treatment by inhaled muco-active drugs or bronchoscopy.TRIAL REGISTRATIONClinicaltrials.gov; NCT01718197, NCT01606826, NCT01750411, NCT01761058, NCT01761630, NCT01716494, and NCT01760915.FUNDINGAstraZeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Sanofi-Genzyme-Regeneron, and TEVA provided financial support for study activities at the Coordinating and Clinical Centers beyond the third year of patient follow-up. These companies had no role in study design or data analysis, and the only restriction on the funds was that they be used to support the SARP initiative.
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- 2024
15. A randomized clinical trial testing digital mindset intervention for knee osteoarthritis pain and activity improvement
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Boswell, Melissa A., Evans, Kris M., Ghandwani, Disha, Hastie, Trevor, Zion, Sean R., Moya, Paula L., Giori, Nicholas J., Hicks, Jennifer L., Crum, Alia J., and Delp, Scott L.
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- 2024
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16. Metformin use and preeclampsia risk in women with diabetes: a two-country cohort analysis
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Gordon, Hannah, Salim, Noor, Tong, Stephen, Walker, Susan, De Silva, Manarangi, Cluver, Catherine, Mehdipour, Parinaz, Hiscock, Richard, Sutherland, Lauren, Doust, Ann, Bergman, Lina, Wikström, Anna-Karin, Lindquist, Anthea, Hesselman, Susanne, and Hastie, Roxanne
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- 2024
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17. Formation of silicic crust on early Earth and young planetary bodies in an Iceland-like setting
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Law, Sally, Hastie, Alan R., Young, Lindsay A., and Thordarson, Thor
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- 2024
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18. Impact of disrespectful maternity care on childbirth complications: a multicentre cross-sectional study in Ethiopia
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Yohannes, Ephrem, Moti, Gonfa, Gelan, Gemechu, Creedy, Debra K., Gabriel, Laura, and Hastie, Carolyn
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- 2024
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19. Phage-specific immunity impairs efficacy of bacteriophage targeting Vancomycin Resistant Enterococcus in a murine model
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Berkson, Julia D., Wate, Claire E., Allen, Garrison B., Schubert, Alyxandria M., Dunbar, Kristin E., Coryell, Michael P., Sava, Rosa L., Gao, Yamei, Hastie, Jessica L., Smith, Emily M., Kenneally, Charlotte R., Zimmermann, Sally K., and Carlson, Jr., Paul E.
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- 2024
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20. A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the USA
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Walters, William A., Ley, Catherine, Hastie, Trevor, Ley, Ruth E., and Parsonnet, Julie
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- 2024
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21. The use of functional appliances for class II malocclusions: a nation-wide cross-sectional survey of orthodontists in Australia
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Hastie Thomas, Goonewardene Mithran, Lee Richard, Naoum Steven, and Razza Mike
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Dentistry ,RK1-715 - Abstract
If detected at the appropriate age, a Class II malocclusion can be improved or camouflaged by utilising functional appliances to manipulate a child’s skeletal growth spurt to advantage.
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- 2024
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22. A randomized clinical trial testing digital mindset intervention for knee osteoarthritis pain and activity improvement
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Melissa A. Boswell, Kris M. Evans, Disha Ghandwani, Trevor Hastie, Sean R. Zion, Paula L. Moya, Nicholas J. Giori, Jennifer L. Hicks, Alia J. Crum, and Scott L. Delp
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
Abstract This randomized clinical trial evaluated the effectiveness of short, digital interventions in improving physical activity and pain for individuals with knee osteoarthritis. We compared a digital mindset intervention, focusing on adaptive mindsets (e.g., osteoarthritis is manageable), to a digital education intervention and a no-intervention group. 408 participants with knee osteoarthritis completed the study online in the US. The mindset intervention significantly improved mindsets compared to both other groups (P
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- 2024
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23. Strategies for the Teaching of Content Courses in Physical Education Teacher Education
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Emi Tsuda, Phillip Ward, Peter Hastie, Bomna Ko, José A. Santiago, Insook Kim, Junyoung Kim, and James D. Ressler
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A teacher cannot teach what they do not know. Previous studies have demonstrated that increasing teachers' content knowledge (common content knowledge [CCK] and specialized content knowledge [SCK]) enhances teachers' teaching effectiveness, which in turn results in better student learning. In the limited curricular space available in physical education teacher education (PETE) programs, maximizing the allocated time for developing content knowledge among preservice teachers is crucial. The purpose of this article is to propose strategies for teaching content courses to develop preservice teachers' content knowledge using examples from volleyball. Various pedagogical strategies to develop content knowledge that can be used in classroom settings (e.g., repeated assessment, scaffolding, and modeling in different forms) are introduced. Increasing the amount of peer teaching and teaching of preK-12 students are also effective strategies to promote preservice teachers' learning of content knowledge and its application.
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- 2024
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24. Academic Learning Time in Physical Education (ALT-PE) during an Adapted Tennis Program for Children with Autism Spectrum Disorders
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Emily E. Munn, Loriane Favoretto Hill, Danielle M. Lang, Sheri J. Brock, Peter Hastie, and Melissa M. Pangelinan
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As the prevalence of autism spectrum disorder (ASD) increases, there is a growing need to develop physical activity interventions that address the behavioral challenges experienced by individuals with ASD. Physical education teachers have employed behavioral supports that add more structure and adapt the environment for individuals with ASD, which are associated with increased engagement for individuals with ASD during PE. The purpose of this study was to quantify motor engaged behaviors (i.e. motor appropriate (MA)), motor inappropriate (MI), motor supported (MS) during skill practice in 18 individuals with ASD (ages 7-19 years) participating in an adapted tennis program (ACEing Autism) using the Academic Learning Time in Physical Education (ALT-PE) instrument. Overall, the supports provided during the program may have enabled participants with ASD to spend more time in MA and MS than MI. Indeed, the participants spent over 50% of their time in MA during the program.
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- 2024
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25. Come Closer: The Effects of Robot Personality on Human Proxemics Behaviours
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Moujahid, Meriam, Robb, David A., Dondrup, Christian, and Hastie, Helen
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Computer Science - Robotics ,H.5 ,I.2 - Abstract
Social Robots in human environments need to be able to reason about their physical surroundings while interacting with people. Furthermore, human proxemics behaviours around robots can indicate how people perceive the robots and can inform robot personality and interaction design. Here, we introduce Charlie, a situated robot receptionist that can interact with people using verbal and non-verbal communication in a dynamic environment, where users might enter or leave the scene at any time. The robot receptionist is stationary and cannot navigate. Therefore, people have full control over their personal space as they are the ones approaching the robot. We investigated the influence of different apparent robot personalities on the proxemics behaviours of the humans. The results indicate that different types of robot personalities, specifically introversion and extroversion, can influence human proxemics behaviours. Participants maintained shorter distances with the introvert robot receptionist, compared to the extrovert robot. Interestingly, we observed that human-robot proxemics were not the same as typical human-human interpersonal distances, as defined in the literature. We therefore propose new proxemics zones for human-robot interaction., Comment: Author Accepted Manuscript- 8 pages, RO-MAN'23, 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), August 2023, Busan, South Korea
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- 2023
26. Feeding the Coffee Habit: A Longitudinal Study of a Robo-Barista
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Lim, Mei Yii, Robb, David A., Wilson, Bruce W., and Hastie, Helen
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Computer Science - Robotics ,H.5 ,I.2 - Abstract
Studying Human-Robot Interaction over time can provide insights into what really happens when a robot becomes part of people's everyday lives. "In the Wild" studies inform the design of social robots, such as for the service industry, to enable them to remain engaging and useful beyond the novelty effect and initial adoption. This paper presents an "In the Wild" experiment where we explored the evolution of interaction between users and a Robo-Barista. We show that perceived trust and prior attitudes are both important factors associated with the usefulness, adaptability and likeability of the Robo-Barista. A combination of interaction features and user attributes are used to predict user satisfaction. Qualitative insights illuminated users' Robo-Barista experience and contribute to a number of lessons learned for future long-term studies., Comment: Author Accepted Manuscript, 8 pages, RO-MAN'23, 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), August 2023, Busan, South Korea
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- 2023
27. We are all Individuals: The Role of Robot Personality and Human Traits in Trustworthy Interaction
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Lim, Mei Yii, Lopes, José David Aguas, Robb, David A., Wilson, Bruce W., Moujahid, Meriam, De Pellegrin, Emanuele, and Hastie, Helen
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Computer Science - Robotics ,Computer Science - Artificial Intelligence ,H.5 ,I.2 - Abstract
As robots take on roles in our society, it is important that their appearance, behaviour and personality are appropriate for the job they are given and are perceived favourably by the people with whom they interact. Here, we provide an extensive quantitative and qualitative study exploring robot personality but, importantly, with respect to individual human traits. Firstly, we show that we can accurately portray personality in a social robot, in terms of extroversion-introversion using vocal cues and linguistic features. Secondly, through garnering preferences and trust ratings for these different robot personalities, we establish that, for a Robo-Barista, an extrovert robot is preferred and trusted more than an introvert robot, regardless of the subject's own personality. Thirdly, we find that individual attitudes and predispositions towards robots do impact trust in the Robo-Baristas, and are therefore important considerations in addition to robot personality, roles and interaction context when designing any human-robot interaction study., Comment: 8 pages, RO-MAN'22, 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), August 2022, Naples, Italy
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- 2023
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28. 'What are you referring to?' Evaluating the Ability of Multi-Modal Dialogue Models to Process Clarificational Exchanges
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Chiyah-Garcia, Javier, Suglia, Alessandro, Eshghi, Arash, and Hastie, Helen
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Computer Science - Computation and Language - Abstract
Referential ambiguities arise in dialogue when a referring expression does not uniquely identify the intended referent for the addressee. Addressees usually detect such ambiguities immediately and work with the speaker to repair it using meta-communicative, Clarificational Exchanges (CE): a Clarification Request (CR) and a response. Here, we argue that the ability to generate and respond to CRs imposes specific constraints on the architecture and objective functions of multi-modal, visually grounded dialogue models. We use the SIMMC 2.0 dataset to evaluate the ability of different state-of-the-art model architectures to process CEs, with a metric that probes the contextual updates that arise from them in the model. We find that language-based models are able to encode simple multi-modal semantic information and process some CEs, excelling with those related to the dialogue history, whilst multi-modal models can use additional learning objectives to obtain disentangled object representations, which become crucial to handle complex referential ambiguities across modalities overall., Comment: Accepted at SIGDIAL'23 (upcoming). Repository with code and experiments available at https://github.com/JChiyah/what-are-you-referring-to
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- 2023
29. A Statistical View of Column Subset Selection
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Sood, Anav and Hastie, Trevor
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Statistics - Methodology ,Computer Science - Data Structures and Algorithms ,Computer Science - Machine Learning - Abstract
We consider the problem of selecting a small subset of representative variables from a large dataset. In the computer science literature, this dimensionality reduction problem is typically formalized as Column Subset Selection (CSS). Meanwhile, the typical statistical formalization is to find an information-maximizing set of Principal Variables. This paper shows that these two approaches are equivalent, and moreover, both can be viewed as maximum likelihood estimation within a certain semi-parametric model. Within this model, we establish suitable conditions under which the CSS estimate is consistent in high dimensions, specifically in the proportional asymptotic regime where the number of variables over the sample size converges to a constant. Using these connections, we show how to efficiently (1) perform CSS using only summary statistics from the original dataset; (2) perform CSS in the presence of missing and/or censored data; and (3) select the subset size for CSS in a hypothesis testing framework.
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- 2023
30. Scalable solution to crossed random effects model with random slopes
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Ghandwani, Disha, Ghosh, Swarnadip, Hastie, Trevor, and Owen, Art B.
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Statistics - Methodology - Abstract
The crossed random effects model is widely used, finding applications in various fields such as longitudinal studies, e-commerce, and recommender systems, among others. However, these models encounter scalability challenges, as the computational time for standard algorithms grows superlinearly with the number N of observations in the data set, commonly $\Omega(N^{3/2})$ or worse. Recent work has developed scalable methods for crossed random effects in linear models and some generalized linear models, but those works only allow for random intercepts. In this paper we devise scalable algorithms for models that include random slopes. This problem brings a substantial difficulty in estimating the random effect covariance matrices in a scalable way. We address that issue by using a variational EM algorithm. In simulations, we see that the proposed method is faster than standard methods. It is also more efficient than ordinary least squares which also has a problem of greatly underestimating the sampling uncertainty in parameter estimates. We illustrate the new method on a large dataset (five million observations) from the online retailer Stitch Fix.
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- 2023
31. Nasopharyngeal SARS-CoV-2 viral load kinetics using digital PCR
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Hastie, Elizabeth, Amogan, Harold, Looney, David, and Mehta, Sanjay R
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Medical Microbiology ,Biomedical and Clinical Sciences ,Infectious Diseases ,Coronaviruses ,Good Health and Well Being ,Sars-CoV-2 ,Viral kinetics ,Digital PCR ,COVID-19 ,Viral decay - Abstract
BackgroundThe relationship between the viral kinetics of SARS-CoV-2 and clinical outcomes remains unclear.MethodsA convenience sample of 955 remnant nasopharyngeal swabs collected during routine care between 11/18/20 and 9/26/21 were analyzed using digital PCR and associated clinical data extracted from the medical record. 18 individuals had >1 sample within 30 days of onset of symptoms.ResultsPaired samples were an average of 6 [range: 0-13] days apart. Four individuals sampled twice on the same day had a median 0.52 log10 viral load difference between samples. Of the remaining, 12 individuals had a decrease in viral load over time, with an average decay of -0.23 log10/day.ConclusionsOur study found a similar rate of viral decay to others, but did not find associations between viral kinetics and clinical outcomes. Larger studies would be useful to support the use of this measurement as a surrogate endpoint for therapeutic studies.
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- 2023
32. Similar But Different: Intimate Partner Violence Experienced by Women and Men
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Roebuck, Benjamin S., McGlinchey, Diana, Lysova, Alexandra V., Hastie, Kristine, and Taylor, Marissa
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- 2024
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33. A Surrogate Model Framework for Explainable Autonomous Behaviour
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Gavriilidis, Konstantinos, Munafo, Andrea, Pang, Wei, and Hastie, Helen
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Computer Science - Robotics - Abstract
Adoption and deployment of robotic and autonomous systems in industry are currently hindered by the lack of transparency, required for safety and accountability. Methods for providing explanations are needed that are agnostic to the underlying autonomous system and easily updated. Furthermore, different stakeholders with varying levels of expertise, will require different levels of information. In this work, we use surrogate models to provide transparency as to the underlying policies for behaviour activation. We show that these surrogate models can effectively break down autonomous agents' behaviour into explainable components for use in natural language explanations.
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- 2023
34. Metformin use and preeclampsia risk in women with diabetes: a two-country cohort analysis
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Hannah Gordon, Noor Salim, Stephen Tong, Susan Walker, Manarangi De Silva, Catherine Cluver, Parinaz Mehdipour, Richard Hiscock, Lauren Sutherland, Ann Doust, Lina Bergman, Anna-Karin Wikström, Anthea Lindquist, Susanne Hesselman, and Roxanne Hastie
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Metformin ,Pregnancy ,Gestational diabetes ,Pre-eclampsia ,Gestational hypertension ,Pregnancy-induced hypertension ,Medicine - Abstract
Abstract Background Metformin is a hypoglycaemic medication that has been proposed to treat or prevent preeclampsia. Combining national birth data from Scotland and Sweden, we investigated whether metformin used during pregnancy was associated with an altered risk of developing a hypertensive disorder of pregnancy. Methods We utilised data from two population-based cohorts: Scotland (2012–2018) and Sweden (2007–2019). Nulliparous women with gestational diabetes or type 2 diabetes who had birth outcome data linked with medications prescribed during pregnancy were included. The association between metformin prescription and hypertensive disorders of pregnancy was characterised using inverse probability weighted regression analysis, adjusting for variables that predict metformin use and potential confounders. Adverse neonatal outcomes were included as secondary outcomes. Results from both countries were then combined in a meta-analysis using a random effects model. Results The Scottish cohort included 3859 women with gestational diabetes or type 2 diabetes. Of these women, 30.8% (n = 1187) received at least one metformin prescription during pregnancy. For Sweden, 7771 women with gestational diabetes were included where 19.3% (1498) used metformin during pregnancy. Metformin prescription was not associated with an altered risk of any hypertensive disorder of pregnancy (Scotland adjusted relative risk (aRR) 0.88 [95% confidence interval (CI) 0.66–1.19]; Sweden aRR 1.08 [95% CI 0.86–1.37]) or preeclampsia (Scotland aRR 1.02 [95% CI 0.66–1.60]; Sweden aRR 1.00 [95% CI 0.72–1.39]). Combining adjusted results in a meta-analysis produced similar findings, with a pooled RR of 0.98 (95% CI 0.79–1.18) for any hypertensive disorder and RR 1.01 ([95% CI 0.73–1.28]) for preeclampsia. For neonatal outcomes, metformin was associated with a reduced risk of birthweight > 4500 g in Scotland (aRR 0.39 [95% CI 0.21–0.71]) but not in Sweden. There was no association between metformin and preterm birth or birthweight
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- 2024
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35. No immunological interference or concerns about safety when seasonal quadrivalent influenza vaccine is co-administered with a COVID-19 mRNA-1273 booster vaccine in adults: A randomized trial
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Abdi Naficy, Adrienne Kuxhausen, Harry Seifert, Andrew Hastie, Brett Leav, Jacqueline Miller, Kate Anteyi, and Agnes Mwakingwe-Omari
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Co-administration ,COVID-19 vaccine ,immunogenicity ,influenza vaccine ,mRNA-1273 ,Immunologic diseases. Allergy ,RC581-607 ,Therapeutics. Pharmacology ,RM1-950 - Abstract
ABSTRACTThe objective of the study was to assess the safety and immunogenicity of mRNA-1273 COVID-19 booster vaccination when co-administered with an egg-based standard dose seasonal quadrivalent influenza vaccine (QIV). This was a phase 3, randomized, open-label study. Eligible adults aged ≥ 18 years were randomly assigned (1:1) to receive mRNA-1273 (50 µg) booster vaccination and QIV 2 weeks apart (Seq group) or concomitantly (Coad group). Primary objectives were non-inferiority of haemagglutinin inhibition (HI) and anti-Spike protein antibody responses in the Coad compared to Seq group. 497/498 participants were randomized and vaccinated in the Seq/Coad groups, respectively. The adjusted geometric mean titer/concentration ratios (95% confidence intervals) (Seq/Coad) for HI antibodies were 1.02 (0.89–1.18) for A/H1N1, 0.93 (0.82–1.05) for A/H3N2, 1.00 (0.89–1.14] for B/Victoria, and 1.04 (0.93–1.17) for B/Yamagata; and 0.98 (0.84–1.13) for anti-Spike antibodies, thus meeting the protocol-specified non-inferiority criteria. The most frequently reported adverse events in both groups were pain at the injection site and myalgia. The 2 groups were similar in terms of the overall frequency, intensity, and duration of adverse events. In conclusion, co-administration of mRNA-1273 booster vaccine with QIV in adults was immunologically non-inferior to sequential administration. Safety and reactogenicity profiles were similar in both groups (clinicaltrials.gov NCT05047770).
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- 2024
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36. The development of an 'Engagement in Physical Education' scale
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Andy Stringfellow, Chih-hsuan Wang, Claudio F. G. Farias, and Peter A. Hastie
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participation ,involvement ,survey ,CFA ,physical education ,Sports ,GV557-1198.995 - Abstract
PurposeThe purpose of this paper is to present a scale that assesses students' perceptions of their engagement in physical education. The scale assesses all four dimensions of engagement (agentic, cognitive, behavioral, and emotional) in order to be consistent with the contemporary notion of engagement used in current educational research.MethodA total of 231 eighth and ninth-grade students (108 boys, Mage = 14.55) completed a 21-item scale, with items taken from previously validated scales, but with an added string relating to physical education lessons. Following model respecification by the examination of standardized residual covariances to remove items, the factor loading for each of the items on the scale was examined.ResultsThe results from a confirmatory factor analysis showed that there was psychometric support for an 18-item survey in which each of the four a priori latent variables was kept in the validation of the four-factor hypothesized model. [χ2 = 226.01, df = 125, χ2/df = 1.808, GFI = .903, RMSEA (90% CI) = .061 (.048–.073)].ConclusionGiven the research on engagement within physical education has been beleaguered by the lack of a robust operational definition, this scale allows for the comprehensive measurement of the different components of engagement.
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- 2024
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37. The South African Statistical Association and its role in science in South Africa
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Inger Fabris-Rotelli, Neill Smit, Cornelis J. Potgieter, Paul Fatti, Renette J. Blignaut, Trevor Hastie, Roelof Coetzer, Yoko Chhana, Niël le Roux, Sugnet Lubbe, Tarylee Reddy, Pravesh Debba, Johan Ferreira, Linda Haines, Christien Thiart, Thomas Farrar, Gary Sharp, Ansie Smit, Ashwell Jenneker, Liesl Morey, Mardé Booyse, Delia North, and Ariane Neethling
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statistics, statistician ,South African Statistical Association ,Stats SA ,Science ,Science (General) ,Q1-390 ,Social Sciences ,Social sciences (General) ,H1-99 - Published
- 2024
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38. Long Covid: a global health issue – a prospective, cohort study set in four continents
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Synne Jenum, Renaud Tamisier, Clark D Russell, Rachel Evans, Piero Valentini, Sylvain Diamantis, Dominique Deplanque, Jordi Rello, Agnes Meybeck, Maxime Hentzien, Clotilde Allavena, André Cabié, Firouzé Bani-Sadr, Patrick Rossignol, Lionel Piroth, Mathieu Blot, Marie-Pierre Debray, François Angoulvant, Marc Leone, Ewen M Harrison, Maria Zambon, Michael Edelstein, Florentia Kaguelidou, Marc Lambert, Olivier Lairez, Tom Solomon, Carrol Gamble, Laura Marsh, Christiana Kartsonaki, Natalie Wright, Behzad Nadjm, Srinivas Murthy, Gail Carson, Jake Dunning, Laura Merson, Peter Horby, Timothy M Uyeki, Piero Olliaro, Guillermo Maestro de la Calle, Stephen R Knight, Thomas M Drake, Marlene Murris, Aurore Bousquet, Kenneth A McLean, Hugues Cordel, Marc Fabre, Laurence Bouillet, Katrina Hann, Xavier Duval, James Lee, Christian Rabaud, Paul Klenerman, Jean-Christophe Lucet, Jean-François Timsit, Jennifer Lee, David J Lowe, Nicolas Terzi, Saad Nseir, Gwenhaël Colin, Steve Webb, Kalynn Kennon, Caroline Mudara, Diana Hernández, Yazdan Yazdanpanah, Jean-François Payen, Samreen Ijaz, Joanne McPeake, Meera Chand, Catherine A Shaw, Cameron J Fairfield, Bruno Levy, Eric D'ortenzio, Pierre Delobel, Tiphaine Goulenok, Bronner P Gonçalves, Arnaud Scherpereel, Danilo Buonsenso, Mark G Pritchard, Susanne Dudman, Adrien Auvet, Caterina Caminiti, Debby Bogaert, Elisabeth Botelho-Nevers, Amandine Gagneux-Brunon, Merce Jourdain, Sue Smith, Jia Wei, Antoine Khalil, Clément Le Bihan, Nathalie Pansu, Vincent Le Moing, Victor Fomin, Christophe Fraser, Daniel Munblit, William Greenhalf, François-Xavier Lescure, Nicolas Carlier, Saye Khoo, Annemarie B Docherty, Christopher A Green, Riinu Pius, Louise Sigfrid, Sophie Halpin, Clare Jackson, Antonia Ho, Malcolm G Semple, Andrew Dagens, Carlo Palmieri, Lance Turtle, Zeno Bisoffi, Thomas Flament, Julie Mankikian, Romain Basmaci, Peter Openshaw, Rob Fowler, Tom Fletcher, Adrien Lemaignen, Pierre Tattevin, Christelle Delmas, Hélène Espérou, Claire Lévy-Marchal, Olivier Picone, Jeanne Sibiude, Cecile Yelnik, Michelle Girvan, Piero L Olliaro, Beatrice Alex, Benjamin Bach, Wendy S Barclay, Graham S Cooke, Ana da Silva Filipe, Alexander J Mentzer, Alison M Meynert, Mahdad Noursadeghi, Shona C Moore, Massimo Palmarini, William A Paxton, Georgios Pollakis, David L Robertson, Vanessa Sancho-Shimizu, Janet T Scott, Shiranee Sriskandan, David Stuart, Charlotte Summers, Emma C Thomson, Ryan S Thwaites, Lance C W Turtle, Hayley Hardwick, Wilna Oosthuyzen, Fiona Griffiths, Jo Dalton, Egle Saviciute, Stephanie Roberts, Janet Harrison, Marie Connor, Gary Leeming, Ross Hendry, Victoria Shaw, Jade Ghosn, Lucille Blumberg, Nicolas Benech, Odile Launay, Yoan Lavie-Badie, Minh Le, Elise Artaud-Macari, Muge Cevik, Nicola Latronico, Mylène Maillet, Didier Laureillard, Ben Morton, Claire Hastie, Nicholas Sedillot, Anne-Sophie Boureau, Laurent Abel, Guillaume Martin-Blondel, Valérie Garrait, Isabelle Delacroix, Andrea Cortegiani, Jean-Benoît Arlet, Raphaël Borie, Kévin Bouiller, Vincent Langlois, Mélanie Roriz, Vincent Dubée, John H Amuasi, Madiha Hashmi, Edwin Jesudason, Jan Cato Holter, Anders Benjamin Kildal, Luis Felipe Reyes, Anna Beltrame, Sulaiman Lakoh, Stéphanie Fry, Lynsey Goodwin, Laurent Plantier, Anna Casey, Denis Malvy, Nina Jamieson, François Dubos, Jean-Sébastien Hulot, Paola Rodari, Frank Bloos, Cécile Tromeur, Paul Loubet, Marina Esposito-Farèse, France Mentré, Valérie Gaborieau, Cécile Goujard, Vincent Thibault, Adam Ali, Sadie Kelly, Fernando A Bozza, Bertrand Dussol, Marion Schneider, Marielle Buisson, Yves Levy, Carine Roy, Walter Picard, Olivier Sanchez, Nazir Lone, Antoine Kimmoun, Roberto Roncon-Albuquerque, Nathan Peiffer-Smadja, Julien Poissy, Lila Bouadma, Bruno Lina, Maude Bouscambert, Alexandre Gaymard, Gilles Peytavin, Jeremie Guedj, Claire Andrejak, Cedric Laouenan, Anissa Chair, Samira Laribi, Marie-Capucine Tellier, Sandrine Couffin-Cadiergues, Ventzislava Petrov-Sanchez, Alpha Diallo, Sarah Tubiana, Patrick Imbert, Emmanuelle Mercier, Waasila Jassat, Arsene Kpangon, Dominique Luton, Simone Piva, Sophie Mahy, Pierre-Adrien Bolze, Sarah Moore, Raphael Favory, Andrea Angheben, Andrea Rossanese, Matthew Hall, Johann Auchabie, Christophe Rapp, Vincent Peigne, Fredrik Müller, Christl A Donnelly, François Goehringer, Elodie Curlier, Catherine Chirouze, Vegard Skogen, Stéphane Jaureguiberry, Laurent Bitker, Hodane Yonis, Laurent Mandelbrot, Jérémie Pasquier, Bato Hammarström, Thushan de Silva, Polina Bugaeva, Julie Chas, Dario Sinatti, Arne Søraas, Murray Wham, Sara Clohisey, Seán Keating, Thibault Chiarabini, Agnes Sommet, Hugues Aumaître, Charlotte Charpentier, Sylvie LeGac, Sarah E McDonald, Jeanne Truong, Anne-Hélène Boivin, Mariachiara Ippolito, Ellen Pauley, Diane Descamps, Sérgio Gaião, Stéphane Lasry, Amanda Rojek, Charlotte Salmon Gandonniere, Sebastien Preau, Benoit Thill, Karine Faure, Denis Garot, Grégory Corvaisier, Elsa Nyamankolly, Merete Ellingjord-Dale, Eva Geraud, Barbara Wanjiru Citarella, Kévin Alexandre, Nathalie Allou, Séverine Ansart, Laurène Azemar, Cecile Azoulay, Delphine Bachelet, Claudine Badr, Valeria Balan, Marie Bartoli, Joaquín Baruch, Jules Bauer, Alexandra Bedossa, Husna Begum, Marine Beluze, Delphine Bergeaud, Giulia Bertoli, Simon Bessis, Sybille Bevilcaqua, Karine Bezulier, Krishna Bhavsar, Laetitia Bodenes, Isabela Bolaños, Olivier Bouchaud, Sabelline Bouchez, Camile Bouisse, Marielle Boyer-Besseyre, Axelle Braconnier, Ingrid G Bustos, Denis Butnaru, Eder Caceres, Cyril Cadoz, Valentine Campana, Pauline Caraux-Paz, Thierry Carmoi, Marie-Christine Carret, Maire-Laure Casanova, Guylaine Castor-Alexandre, François-Xavier Catherine, Minerva Cervantes-Gonzalez, Catherine Chakveatze, Jean-Marc Chapplain, Antoine Cheret, Bernard Cholley, Marie-Charlotte Chopin, Roxane Courtois, Stéphanie Cousse, Alexa Debard, Nathalie DeCastro, Romain Decours, Eve Defous, Karen Delavigne, Elisa Demonchy, Emmanuelle Denis, Mathilde Desvallées, Kévin Didier, Jean-Luc Diehl, Vincent Dinot, Fara Diop, Alphonsine Diouf, Félix Djossou, Céline Dorival, Nathalie Dournon, Murray Dryden, Alexandre Ducancelle, Paul Dunand, Brigitte Elharrar, Philippine Eloy, Isabelle Enderle, Ilka Engelmann, Vincent Enouf, Olivier Epaulard, Manuel Etienne, Isabelle Fabre, François-Xavier Ferrand, Eglantine Ferrand Devouge, Nicolas Ferriere, Céline Ficko, Erwan Fourn, Rostane Gaci, Jean-Charles Gagnard, Esteban Garcia-Gallo, Tristan Gigante, Guillermo Giordano, Valérie Gissot, Petr Glybochko, Marie Gominet, Isabelle Gorenne, Laure Goubert, Pascal Granier, Segolène Greffe, Martin Guego, Romain Guery, Anne Guillaumot, Laurent Guilleminault, Thomas Guimard, Ali Hachemi, Nadir Hadri, Rebecca Hamidfar, Lars Heggelund, Rupert Higgins, Hikombo Hitoto, Alexandre Hoctin, Isabelle Hoffmann, Ikram Houas, Margaux Isnard, Danielle Jaafar, Salma Jaafoura, Julien Jabot, Florence Jego, Cédric Joseph, Ouifiya Kafif, Sabina Kali, Younes Kerroumi, Marie Lachatre, Marie Lacoste, Marie Lagrange, Fabrice Laine, Antonio Lalueza, Marie Langelot-Richard, Delphine Lariviere, Andy Law, Laurent Lefebvre, Bénédicte Lefebvre, Benjamin Lefèvre, Jean-Daniel Lelievre, Véronique Lemee, Anthony Lemeur, Quentin Lepiller, Olivier Lesens, Mathieu Lesouhaitier, Geoffrey Liegeon, Guillaume Lingas, Sylvie Lion-Daolio, Marine Livrozet, Bouchra Loufti, Guillame Louis, Liem Luong, Moïse Machado, Gabriel Macheda, Rafael Mahieu, Thomas Maitre, Victoria Manda, Aldric Manuel, Samuel Markowicz, Martin Martinot, Mathieu Mattei, Laurence Maulin, Thierry Mazzoni, Cécile Mear-Passard, Antoine Merckx, Mayka Mergeay-Fabre, Vanina Meysonnier, Mehdi Mezidi, Isabelle Michelet, Lucia Moro, Julien Moyet, Jimmy Mullaert, Nadège Neant, Nikita Nekliudov, Anthony Nghi, Duc Nguyen, Nadia Ouamara, Rachida Ouissa, Eric Oziol, Justine Pages Maïder Pagadoy, Aurélie Papadopoulos, Bruno Pastene, Christelle Paul, Florent Peelman, Daniel Perez, Thomas Perpoint, Vincent Pestre, Ryadh Pokeerbux, Diane Ponscarme, Marie Rafiq, Blandine Rammaert, Stanislas Rebaudet, Sarah Redl, Anne-Sophie Resseguier, Matthieu Revest, Laurent Richier, Patrick Rispal, Karine Risso, Olivier Robineau, Manuel Rosa-Calatrava, Benoît Roze, Hélène Salvator, Pierre-François Sandrine, Benjamine Sarton, Eric Senneville, Albert Sotto, Sarah Stabler, Andrey Svistunov, Coralie Tardivon, François Téoulé, Olivier Terrier, Simon-Djamel Thiberville, Peter S Timashev, Noémie Tissot, Tiffany Trouillon, Christelle Tual, Noémie Vanel, Charline Vauchy, Aurélie Veislinger, Fanny Vuotto, Aurélie Wiedemann, Marion Zabbe, David Zucman, Silvio Hamacher, Ekaterina Pazukhina, Allegra Chatterjee, Kyle Gomez, Matteo Puntoni, Oksana Kruglova, Yock Ping Chow, Yash Doshi, Sara Isabel Duque Vallejo, Elsa D Ibáñez-Prada, Yuli V Fuentes, Margaret E O'Hara, Tigist Menkir, Amal Abrous, Younes Ait Tamlihat, Aliya Mohammed Alameen, Marta Alessi, Kazali Enagnon Alidjnou, Jean Baptiste Assie, Eyvind W Axelsen, John Kenneth Baillie, José Luis Bernal Sobrino, Sonja Hjellegjerde Brunvoll, Roar Bævre-Jensen, Jose Andres Calvache, Léo Chenard, Juan Luis Cruz Bermúdez, Jaime Cruz Rojo, Charlene Da Silveira, John Arne Dahl, Etienne De Montmollin, Cristina De Rose, Fernanda Dias Da Silva, Thomas Drake, Amiel A Dror, Anne Margarita Dyrhol-Riise, Linn Margrete Eggesbø, Mohammed El Sanharawi, William Finlayson, Aline-Marie Florence, Linda Gail Skeie, Noelia García Barrio, Anatoliy Gavrylov, Louis Gerbaud Morlaes, Yanay Gorelik, Mette Stausland Istre, Silje Bakken Jørgensen, Karl Trygve Kalleberg, Beathe Kiland Granerud, Eyrun Floerecke Kjetland Kjetland, Gry Kloumann Bekken, Galyna Kutsyna, Nadhem Lafhej, Cyril Le Bris, Georges Le Falher, Lucie Le Fevre, Quentin Le Hingrat, Marion Le Maréchal, Soizic Le Mestre, Gwenaël Le Moal, Hervé Le Nagard, Sophie Letrou, Wei Shen Lim, Andreas Lind, Carlos Lumbreras Bermejo, Miles Lunn, Olga Martynenko, Roberta Meta, Lina Morales Cely, Clara Mouton Perrot, Alamin Mustafa, Karl Erik Müller, Ebrahim Ndure, Anders Benteson Nygaard, Claudia Milena Orozco-Chamorro, Paul Otiku, Miguel Pedrera Jiménez, Frank Olav Pettersen, Chiara Piubelli, Víctor Quirós González, Else Quist-Paulsen, Dag Henrik Reikvam, Antonia Ricchiuto, Aleksander Rygh Holten, Nadia Saidani, Pablo Serrano Balazote, Nassima Si Mohammed, Lene Bergendal Solberg, Edouard Soum, Elisabetta Spinuzza, Trude Steinsvik, Birgitte Stiksrud, Mathew Thorpe, Vadim Tieroshyn, Kristian Tonby, Anders Tveita, Sylvie Van Der Werf, Paul Henri Wicky, Ibrahim Richard Bangura, Leonardo Bastos, Daniel Cassaglia, Barbara Citarella, Sarah Duque, Anne Margarita Dyrhol Riise, Annelies Gillesen, Bronner P Goncalvez, Margareta O’Hara, Lars Hegelund, Aquiles Henriquez Trujillo, Elsa D Ibañez, Jane Ireson, Oksana Krugalova, Sam Lissaeur, Sinnadurai Manohan, Prasan K Panda, Daniel R Plotkin, Liliana Resende, Sergio Ruiz Saltana, Steffi Ryckaert, Girish Sindhwani Pulm, and Caroline Vika
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Medicine (General) ,R5-920 ,Infectious and parasitic diseases ,RC109-216 - Abstract
Introduction A proportion of people develop Long Covid after acute COVID-19, but with most studies concentrated in high-income countries (HICs), the global burden is largely unknown. Our study aims to characterise long-term COVID-19 sequelae in populations globally and compare the prevalence of reported symptoms in HICs and low-income and middle-income countries (LMICs).Methods A prospective, observational study in 17 countries in Africa, Asia, Europe and South America, including adults with confirmed COVID-19 assessed at 2 to
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- 2024
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39. Influence of Th1 versus Th2 immune bias on viral, pathological, and immunological dynamics in SARS-CoV-2 variant-infected human ACE2 knock-in miceResearch in context
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Shailendra Kumar Verma, Fernanda Ana-Sosa-Batiz, Julia Timis, Norazizah Shafee, Erin Maule, Paolla Beatriz Almeida Pinto, Chris Conner, Kristen M. Valentine, Dale O. Cowley, Robyn Miller, Annie Elong Ngono, Linda Tran, Krithik Varghese, Rúbens Prince Dos Santos Alves, Kathryn M. Hastie, Erica Ollmann Saphire, David R. Webb, Kurt Jarnagin, Kenneth Kim, and Sujan Shresta
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Mouse model ,Delta ,Omicron BA.1 ,CD8 T cells ,CD4 T cells ,B cells ,Medicine ,Medicine (General) ,R5-920 - Abstract
Summary: Background: Mouse models that recapitulate key features of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection are important tools for understanding complex interactions between host genetics, immune responses, and SARS-CoV-2 pathogenesis. Little is known about how predominantly cellular (Th1 type) versus humoral (Th2 type) immune responses influence SARS-CoV-2 dynamics, including infectivity and disease course. Methods: We generated knock-in (KI) mice expressing human ACE2 (hACE2) and/or human TMPRSS2 (hTMPRSS2) on Th1-biased (C57BL/6; B6) and Th2-biased (BALB/c) genetic backgrounds. Mice were infected intranasally with SARS-CoV-2 Delta (B.1.617.2) or Omicron BA.1 (B.1.1.529) variants, followed by assessment of disease course, respiratory tract infection, lung histopathology, and humoral and cellular immune responses. Findings: In both B6 and BALB/c mice, hACE2 expression was required for infection of the lungs with Delta, but not Omicron BA.1. Disease severity was greater in Omicron BA.1-infected hTMPRSS2-KI and double-KI BALB/c mice compared with B6 mice, and in Delta-infected double-KI B6 and BALB/c mice compared with hACE2-KI mice. hACE2-KI B6 mice developed more severe lung pathology and more robust SARS-CoV-2-specific splenic CD8 T cell responses compared with hACE2-KI BALB/c mice. There were no notable differences between the two genetic backgrounds in plasma cell, germinal center B cell, or antibody responses to SARS-CoV-2. Interpretation: SARS-CoV-2 Delta and Omicron BA.1 infection, disease course, and CD8 T cell response are influenced by the host genetic background. These humanized mice hold promise as important tools for investigating the mechanisms underlying the heterogeneity of SARS-CoV-2-induced pathogenesis and immune response. Funding: This work was funded by NIH U19 AI142790-02S1, the GHR Foundation, the Arvin Gottleib Foundation, and the Overton family (to SS and EOS); Prebys Foundation (to SS); NIH R44 AI157900 (to KJ); and by an American Association of Immunologists Career Reentry Fellowship (FASB).
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- 2024
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40. Assessing the Effectiveness of Drinking Water Consolidation in Ensuring the Human Right to Water in California, USA
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Hastie, Allisa G., Osman, Khalid K., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Desjardins, Serge, editor, Azimi, Amir Hossein, editor, and Poitras, Gérard J., editor
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- 2024
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41. Underwater Noise of Two Operational Tidal Stream Turbines: A Comparison
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Risch, Denise, Marmo, Brett, van Geel, Nienke C. F., Gillespie, Douglas, Hastie, Gordon, Sparling, Carol, Onoufriou, Joe, Wilson, Ben, Popper, Arthur N., Section editor, Popper, Arthur N., editor, Sisneros, Joseph A., editor, Hawkins, Anthony D., editor, and Thomsen, Frank, editor
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- 2024
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42. Utilizing Sport Education During Off-Season High School Golf Team Preparation: A Case Study.
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Layne, Todd, Simonton, Kelly, Hastie, Peter, and Brunsdon, Jamie
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GOLF training ,PHYSICAL training & conditioning ,INSTRUCTIONAL systems design ,EMOTIONS ,CLASSROOM environment - Abstract
Purpose: Limited research has examined the Sport Education instructional model and its use with high school athletic teams. The purpose of this study was to see if the model could be utilized as an effective approach to preparing and training youth golf athletes in a motivating way, specifically in the off-season. Method: Participants (N = 9) were placed on teams for a total of eight practice sessions. A mixed-method analysis via survey analysis of motivational basic needs, emotions, and competencies, and focus group interviews occurred. Results: Interviews revealed that the Sport Education format enhanced enjoyment and group connection. Survey data indicated that autonomy support from instructor, enjoyment, and all three motivational needs (i.e., competence, relatedness, autonomy) trended upward. Shame, anger, and anxiety trended down. Discussion/Conclusion: The Sport Education model provides a unique opportunity for coaches to create a learning environment that is friendly, fun, and supportive of player development. [ABSTRACT FROM AUTHOR]
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- 2024
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43. Effect of Immune-Modulatory Interventions on Asymptomatic Cytomegalovirus Shedding During Suppressive Antiretroviral Therapy
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Hastie, Elizabeth, Moser, Carlee, Sun, Xin, Lennox, Jeffrey, Hsue, Priscilla Y, Bosch, Ronald J, Deeks, Steven, Meneses, Milenka V, Lederman, Michael M, Hunt, Peter, Henrich, Timothy J, Marconi, Vincent C, and Gianella, Sara
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Medical Microbiology ,Biomedical and Clinical Sciences ,Immunology ,Clinical Research ,Infectious Diseases ,HIV/AIDS ,Prevention ,Sexually Transmitted Infections ,Clinical Trials and Supportive Activities ,2.1 Biological and endogenous factors ,Evaluation of treatments and therapeutic interventions ,6.1 Pharmaceuticals ,Aetiology ,Infection ,Good Health and Well Being ,Male ,Humans ,Female ,Cytomegalovirus ,Cytomegalovirus Infections ,DNA ,Viral ,HIV Infections ,HIV ,Inflammation ,Virus Shedding ,CMV ,immune modulators ,ruxolitinib ,sirolimus ,Biological Sciences ,Medical and Health Sciences ,Microbiology ,Biological sciences ,Biomedical and clinical sciences ,Health sciences - Abstract
Long-term consequences of human immunodeficiency virus (HIV) are likely the result of persistent inflammation and immune dysfunction of which cytomegalovirus (CMV) is a known contributor. We leveraged 2 AIDS Clinical Trials Group clinical trials exploring the effects of immune modulators (ruxolitinib and sirolimus) on inflammation in people with HIV on antiretroviral therapy to determine whether these interventions affected CMV shedding at various mucosal sites. Analyzing 635 mucosal samples collected, we found no significant difference in CMV levels across study arms or time points. Men had more CMV shedding than women. We did confirm an association between higher CMV DNA and immune markers associated with HIV persistence and HIV-associated mortality rates.
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- 2023
44. Reduced quantity and function of pneumococcal antibodies are associated with exacerbations of COPD in SPIROMICS.
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LaFon, David, Woo, Han, Fedarko, Neal, Azar, Antoine, Hill, Harry, Tebo, Anne, Martins, Thomas, Han, MeiLan, Krishnan, Jerry, Ortega, Victor, Kaner, Robert, Hastie, Annette, ONeal, Wanda, Couper, David, Woodruff, Prescott, Curtis, Jeffrey, Hansel, Nadia, Nahm, Moon, Dransfield, Mark, Putcha, Nirupama, and Barjaktarevic, Igor
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Antibodies ,Immunity ,Immunoglobulin G ,Opsonization ,Streptococcus pneumoniae ,Humans ,Immunoglobulin G ,Streptococcus pneumoniae ,Vaccination ,Immunologic Tests ,Antibodies ,Bacterial ,Pulmonary Disease ,Chronic Obstructive ,Pneumococcal Vaccines ,Pneumococcal Infections - Abstract
While hypogammaglobulinemia is associated with COPD exacerbations, it is unknown whether frequent exacerbators have specific defects in antibody production/function. We hypothesized that reduced quantity/function of serum pneumococcal antibodies correlate with exacerbation risk in the SPIROMICS cohort. We measured total pneumococcal IgG in n = 764 previously vaccinated participants with COPD. In a propensity-matched subset of n = 200 with vaccination within five years (n = 50 without exacerbations in the previous year; n = 75 with one, n = 75 with ≥2), we measured pneumococcal IgG for 23 individual serotypes, and pneumococcal antibody function for 4 serotypes. Higher total pneumococcal IgG, serotype-specific IgG (17/23 serotypes), and antibody function (3/4 serotypes) were independently associated with fewer prior exacerbations. Higher pneumococcal IgG (5/23 serotypes) predicted lower exacerbation risk in the following year. Pneumococcal antibodies are inversely associated with exacerbations, supporting the presence of immune defects in frequent exacerbators. With further study, pneumococcal antibodies may be useful biomarkers for immune dysfunction in COPD.
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- 2023
45. SARS-CoV-2 Omicron (B.1.1.529) shows minimal neurotropism in a double-humanized mouse model
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Alves, Rubens Prince Dos Santos, Wang, Ying-Ting, Mikulski, Zbigniew, McArdle, Sara, Shafee, Norazizah, Valentine, Kristen M, Miller, Robyn, Verma, Shailendra Kumar, Batiz, Fernanda Ana Sosa, Maule, Erin, Nguyen, Michael N, Timis, Julia, Mann, Colin, Zandonatti, Michelle, Alarcon, Suzie, Rowe, Jenny, Kronenberg, Mitchell, Weiskopf, Daniela, Sette, Alessandro, Hastie, Kathryn, Saphire, Erica Ollmann, Festin, Stephen, Kim, Kenneth, and Shresta, Sujan
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Biomedical and Clinical Sciences ,Immunology ,Emerging Infectious Diseases ,Lung ,Infectious Diseases ,Coronaviruses ,Biodefense ,2.1 Biological and endogenous factors ,Aetiology ,Infection ,Good Health and Well Being ,Animals ,Humans ,Mice ,SARS-CoV-2 ,COVID-19 ,Brain ,Antiviral Agents ,Disease Models ,Animal ,Omicron ,Neurotropism ,Mouse model ,Human ACE2 ,Human CD34 immune cells ,T cell ,NCG ,Microbiology ,Medical Microbiology ,Pharmacology and Pharmaceutical Sciences ,Virology ,Medical microbiology ,Pharmacology and pharmaceutical sciences - Abstract
Although severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) initially infects the respiratory tract, it also directly or indirectly affects other organs, including the brain. However, little is known about the relative neurotropism of SARS-CoV-2 variants of concern (VOCs), including Omicron (B.1.1.529), which emerged in November 2021 and has remained the dominant pathogenic lineage since then. To address this gap, we examined the relative ability of Omicron, Beta (B.1.351), and Delta (B.1.617.2) to infect the brain in the context of a functional human immune system by using human angiotensin-converting enzyme 2 (hACE2) knock-in triple-immunodeficient NGC mice with or without reconstitution with human CD34+ stem cells. Intranasal inoculation of huCD34+-hACE2-NCG mice with Beta and Delta resulted in productive infection of the nasal cavity, lungs, and brain on day 3 post-infection, but Omicron was surprisingly unique in its failure to infect either the nasal tissue or brain. Moreover, the same infection pattern was observed in hACE2-NCG mice, indicating that antiviral immunity was not responsible for the lack of Omicron neurotropism. In independent experiments, we demonstrate that nasal inoculation with Beta or with D614G, an ancestral SARS-CoV-2 with undetectable replication in huCD34+-hACE2-NCG mice, resulted in a robust response by human innate immune cells, T cells, and B cells, confirming that exposure to SARS-CoV-2, even without detectable infection, is sufficient to induce an antiviral immune response. Collectively, these results suggest that modeling of the neurologic and immunologic sequelae of SARS-CoV-2 infection requires careful selection of the appropriate SARS-CoV-2 strain in the context of a specific mouse model.
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- 2023
46. RbX: Region-based explanations of prediction models
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Lemhadri, Ismael, Li, Harrison H., and Hastie, Trevor
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Statistics - Machine Learning ,Computer Science - Machine Learning - Abstract
We introduce region-based explanations (RbX), a novel, model-agnostic method to generate local explanations of scalar outputs from a black-box prediction model using only query access. RbX is based on a greedy algorithm for building a convex polytope that approximates a region of feature space where model predictions are close to the prediction at some target point. This region is fully specified by the user on the scale of the predictions, rather than on the scale of the features. The geometry of this polytope - specifically the change in each coordinate necessary to escape the polytope - quantifies the local sensitivity of the predictions to each of the features. These "escape distances" can then be standardized to rank the features by local importance. RbX is guaranteed to satisfy a "sparsity axiom," which requires that features which do not enter into the prediction model are assigned zero importance. At the same time, real data examples and synthetic experiments show how RbX can more readily detect all locally relevant features than existing methods., Comment: 13 pages, 4 figures
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- 2022
47. Developing a Natural History Model for Duchenne Muscular Dystrophy
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Broomfield, Jonathan, Hill, M., Chandler, F., Crowther, M. J., Godfrey, J., Guglieri, M., Hastie, J., Larkindale, J., Mumby-Croft, J., Reuben, E., Woodcock, F., and Abrams, K. R.
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- 2024
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48. Formation of silicic crust on early Earth and young planetary bodies in an Iceland-like setting
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Sally Law, Alan R. Hastie, Lindsay A. Young, and Thor Thordarson
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Geology ,QE1-996.5 ,Environmental sciences ,GE1-350 - Abstract
Abstract Four billion years ago, Earth’s surface was covered with a thick basaltic crust and, similar to other rocky planets and the Moon, parts of this basaltic crust underwent partial melting to produce silicic crust. On Earth, silicic crust grew into the continents. An analogue of a pre-subduction early Earth and rocky planetary bodies is found in Iceland, where poorly understood granitic rocks are encased in thick basaltic crust away from any active subduction zone. Here, we investigate these Icelandic granitoids to understand the mechanisms that generated the Earth’s oldest continents, and silicic rocks on Mars and Venus. New geochemical data from silicic Icelandic intrusions, show that the granitoids are formed through partial melting of the Icelandic crust, but are compositionally unlike early Earth continental material. We show that intra-crustal partial melting of basalt can potentially form silicic material on other planetary bodies but cannot produce the first continents on Earth.
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- 2024
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49. Impact of disrespectful maternity care on childbirth complications: a multicentre cross-sectional study in Ethiopia
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Ephrem Yohannes, Gonfa Moti, Gemechu Gelan, Debra K. Creedy, Laura Gabriel, and Carolyn Hastie
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Central Ethiopia ,Childbirth related complications ,Cross-sectional ,Disrespectful maternity care ,Gynecology and obstetrics ,RG1-991 - Abstract
Abstract Background Globally, disrespectful, and abusive childbirth practices negatively impact women’s health, create barriers to accessing health facilities, and contribute to poor birth experiences and adverse outcomes for both mothers and newborns. However, the degree to which disrespectful maternity care is associated with complications during childbirth is poorly understood, particularly in Ethiopia. Aim To determine the extent to which disrespectful maternity care is associated with maternal and neonatal-related complications in central Ethiopia. Methods A multicentre cross-sectional study was conducted in the West Shewa Zone of Oromia, Ethiopia. The sample size was determined using the single population proportion formula. Participants (n = 440) were selected with a simple random sampling technique using computer-generated random numbers. Data were collected through face-to-face interviews with a pretested questionnaire and were entered into Epidata and subsequently exported to STATA version 17 for the final analysis. Analyses included descriptive statistics and binary logistic regression, with a 95% confidence interval (CI) and an odds ratio (OR) of 0.05. Co-founders were controlled by adjusting for maternal sociodemographic characteristics. The primary exposure was disrespectful maternity care; the main outcomes were maternal and neonatal-related complications. Results Disrespectful maternity care was reported by 344 women (78.2%) [95% CI: 74–82]. Complications were recorded in one-third of mothers (33.4%) and neonates (30%). Disrespectful maternity care was significantly associated with maternal (AOR = 2.22, 95% CI: 1.29, 3.8) and neonatal-related complications (AOR = 2.78, 95% CI: 1.54, 5.04). Conclusion The World Health Organization advocates respectful maternal care during facility-based childbirth to improve the quality of care and outcomes. However, the findings of this study indicated high mistreatment and abuse during childbirth in central Ethiopia and a significant association between such mistreatment and the occurrence of both maternal and neonatal complications during childbirth. Therefore, healthcare professionals ought to prioritise respectful maternity care to achieve improved birth outcomes and alleviate mistreatment and abuse within the healthcare sector.
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- 2024
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50. A common polymorphism in the Intelectin-1 gene influences mucus plugging in severe asthma
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Jamie L. Everman, Satria P. Sajuthi, Maude A. Liegeois, Nathan D. Jackson, Erik H. Collet, Michael C. Peters, Maurizio Chioccioli, Camille M. Moore, Bhavika B. Patel, Nathan Dyjack, Roger Powell, Cydney Rios, Michael T. Montgomery, Celeste Eng, Jennifer R. Elhawary, Angel C. Y. Mak, Donglei Hu, Scott Huntsman, Sandra Salazar, Luigi Feriani, Ana Fairbanks-Mahnke, Gianna L. Zinnen, Cole R. Michel, Joe Gomez, Xing Zhang, Vivian Medina, Hong Wei Chu, Pietro Cicuta, Erin D. Gordon, Pamela Zeitlin, Victor E. Ortega, Nichole Reisdorph, Eleanor M. Dunican, Monica Tang, Brett M. Elicker, Travis S. Henry, Eugene R. Bleecker, Mario Castro, Serpil C. Erzurum, Elliot Israel, Bruce D. Levy, David T. Mauger, Deborah A. Meyers, Kaharu Sumino, David S. Gierada, Annette T. Hastie, Wendy C. Moore, Loren C. Denlinger, Nizar N. Jarjour, Mark L. Schiebler, Sally E. Wenzel, Prescott G. Woodruff, Jose Rodriguez-Santana, Chad G. Pearson, Esteban G. Burchard, John V. Fahy, and Max A. Seibold
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Science - Abstract
Abstract By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma.
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- 2024
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