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1. Gradient flow of phase transitions with fixed contact angle

Author: Marshall-Stevens, Kobe, Takada, Mayu, Tonegawa, Yoshihiro, and Workman, Myles
Subjects: Mathematics - Analysis of PDEs, Mathematics - Differential Geometry, 53E10, 49Q20, 35K20
Abstract: We study the gradient flow of the Allen-Cahn equation with fixed boundary contact angle in Euclidean domains for initial data with bounded energy. Under general assumptions, we establish both interior and boundary convergence properties for the solutions and associated energy measures. Under various boundary non-concentration assumptions, we show that, for almost every time, the associated limiting varifolds satisfy generalised contact angle conditions and have bounded first variation, as well as deducing that the trace of the limit of the solutions coincides with the limit of their traces. Moreover, we derive an Ilmanen type monotonicity formula, for initial data with bounded energy, valid for the associated energy measures up to the boundary., Comment: 24 pages, 2 figures
Published: 2024

2. GPT-4o System Card

Author: OpenAI, Hurst, Aaron, Lerer, Adam, Goucher, Adam P., Perelman, Adam, Ramesh, Aditya, Clark, Aidan, Ostrow, AJ, Welihinda, Akila, Hayes, Alan, Radford, Alec, Mądry, Aleksander, Baker-Whitcomb, Alex, Beutel, Alex, Borzunov, Alex, Carney, Alex, Chow, Alex, Kirillov, Alex, Nichol, Alex, Paino, Alex, Renzin, Alex, Passos, Alex Tachard, Kirillov, Alexander, Christakis, Alexi, Conneau, Alexis, Kamali, Ali, Jabri, Allan, Moyer, Allison, Tam, Allison, Crookes, Amadou, Tootoochian, Amin, Tootoonchian, Amin, Kumar, Ananya, Vallone, Andrea, Karpathy, Andrej, Braunstein, Andrew, Cann, Andrew, Codispoti, Andrew, Galu, Andrew, Kondrich, Andrew, Tulloch, Andrew, Mishchenko, Andrey, Baek, Angela, Jiang, Angela, Pelisse, Antoine, Woodford, Antonia, Gosalia, Anuj, Dhar, Arka, Pantuliano, Ashley, Nayak, Avi, Oliver, Avital, Zoph, Barret, Ghorbani, Behrooz, Leimberger, Ben, Rossen, Ben, Sokolowsky, Ben, Wang, Ben, Zweig, Benjamin, Hoover, Beth, Samic, Blake, McGrew, Bob, Spero, Bobby, Giertler, Bogo, Cheng, Bowen, Lightcap, Brad, Walkin, Brandon, Quinn, Brendan, Guarraci, Brian, Hsu, Brian, Kellogg, Bright, Eastman, Brydon, Lugaresi, Camillo, Wainwright, Carroll, Bassin, Cary, Hudson, Cary, Chu, Casey, Nelson, Chad, Li, Chak, Shern, Chan Jun, Conger, Channing, Barette, Charlotte, Voss, Chelsea, Ding, Chen, Lu, Cheng, Zhang, Chong, Beaumont, Chris, Hallacy, Chris, Koch, Chris, Gibson, Christian, Kim, Christina, Choi, Christine, McLeavey, Christine, Hesse, Christopher, Fischer, Claudia, Winter, Clemens, Czarnecki, Coley, Jarvis, Colin, Wei, Colin, Koumouzelis, Constantin, Sherburn, Dane, Kappler, Daniel, Levin, Daniel, Levy, Daniel, Carr, David, Farhi, David, Mely, David, Robinson, David, Sasaki, David, Jin, Denny, Valladares, Dev, Tsipras, Dimitris, Li, Doug, Nguyen, Duc Phong, Findlay, Duncan, Oiwoh, Edede, Wong, Edmund, Asdar, Ehsan, Proehl, Elizabeth, Yang, Elizabeth, Antonow, Eric, Kramer, Eric, Peterson, Eric, Sigler, Eric, Wallace, Eric, Brevdo, Eugene, Mays, Evan, Khorasani, Farzad, Such, Felipe Petroski, Raso, Filippo, Zhang, Francis, von Lohmann, Fred, Sulit, Freddie, Goh, Gabriel, Oden, Gene, Salmon, Geoff, Starace, Giulio, Brockman, Greg, Salman, Hadi, Bao, Haiming, Hu, Haitang, Wong, Hannah, Wang, Haoyu, Schmidt, Heather, Whitney, Heather, Jun, Heewoo, Kirchner, Hendrik, Pinto, Henrique Ponde de Oliveira, Ren, Hongyu, Chang, Huiwen, Chung, Hyung Won, Kivlichan, Ian, O'Connell, Ian, Osband, Ian, Silber, Ian, Sohl, Ian, Okuyucu, Ibrahim, Lan, Ikai, Kostrikov, Ilya, Sutskever, Ilya, Kanitscheider, Ingmar, Gulrajani, Ishaan, Coxon, Jacob, Menick, Jacob, Pachocki, Jakub, Aung, James, Betker, James, Crooks, James, Lennon, James, Kiros, Jamie, Leike, Jan, Park, Jane, Kwon, Jason, Phang, Jason, Teplitz, Jason, Wei, Jason, Wolfe, Jason, Chen, Jay, Harris, Jeff, Varavva, Jenia, Lee, Jessica Gan, Shieh, Jessica, Lin, Ji, Yu, Jiahui, Weng, Jiayi, Tang, Jie, Yu, Jieqi, Jang, Joanne, Candela, Joaquin Quinonero, Beutler, Joe, Landers, Joe, Parish, Joel, Heidecke, Johannes, Schulman, John, Lachman, Jonathan, McKay, Jonathan, Uesato, Jonathan, Ward, Jonathan, Kim, Jong Wook, Huizinga, Joost, Sitkin, Jordan, Kraaijeveld, Jos, Gross, Josh, Kaplan, Josh, Snyder, Josh, Achiam, Joshua, Jiao, Joy, Lee, Joyce, Zhuang, Juntang, Harriman, Justyn, Fricke, Kai, Hayashi, Kai, Singhal, Karan, Shi, Katy, Karthik, Kavin, Wood, Kayla, Rimbach, Kendra, Hsu, Kenny, Nguyen, Kenny, Gu-Lemberg, Keren, Button, Kevin, Liu, Kevin, Howe, Kiel, Muthukumar, Krithika, Luther, Kyle, Ahmad, Lama, Kai, Larry, Itow, Lauren, Workman, Lauren, Pathak, Leher, Chen, Leo, Jing, Li, Guy, Lia, Fedus, Liam, Zhou, Liang, Mamitsuka, Lien, Weng, Lilian, McCallum, Lindsay, Held, Lindsey, Ouyang, Long, Feuvrier, Louis, Zhang, Lu, Kondraciuk, Lukas, Kaiser, Lukasz, Hewitt, Luke, Metz, Luke, Doshi, Lyric, Aflak, Mada, Simens, Maddie, Boyd, Madelaine, Thompson, Madeleine, Dukhan, Marat, Chen, Mark, Gray, Mark, Hudnall, Mark, Zhang, Marvin, Aljubeh, Marwan, Litwin, Mateusz, Zeng, Matthew, Johnson, Max, Shetty, Maya, Gupta, Mayank, Shah, Meghan, Yatbaz, Mehmet, Yang, Meng Jia, Zhong, Mengchao, Glaese, Mia, Chen, Mianna, Janner, Michael, Lampe, Michael, Petrov, Michael, Wu, Michael, Wang, Michele, Fradin, Michelle, Pokrass, Michelle, Castro, Miguel, de Castro, Miguel Oom Temudo, Pavlov, Mikhail, Brundage, Miles, Wang, Miles, Khan, Minal, Murati, Mira, Bavarian, Mo, Lin, Molly, Yesildal, Murat, Soto, Nacho, Gimelshein, Natalia, Cone, Natalie, Staudacher, Natalie, Summers, Natalie, LaFontaine, Natan, Chowdhury, Neil, Ryder, Nick, Stathas, Nick, Turley, Nick, Tezak, Nik, Felix, Niko, Kudige, Nithanth, Keskar, Nitish, Deutsch, Noah, Bundick, Noel, Puckett, Nora, Nachum, Ofir, Okelola, Ola, Boiko, Oleg, Murk, Oleg, Jaffe, Oliver, Watkins, Olivia, Godement, Olivier, Campbell-Moore, Owen, Chao, Patrick, McMillan, Paul, Belov, Pavel, Su, Peng, Bak, Peter, Bakkum, Peter, Deng, Peter, Dolan, Peter, Hoeschele, Peter, Welinder, Peter, Tillet, Phil, Pronin, Philip, Tillet, Philippe, Dhariwal, Prafulla, Yuan, Qiming, Dias, Rachel, Lim, Rachel, Arora, Rahul, Troll, Rajan, Lin, Randall, Lopes, Rapha Gontijo, Puri, Raul, Miyara, Reah, Leike, Reimar, Gaubert, Renaud, Zamani, Reza, Wang, Ricky, Donnelly, Rob, Honsby, Rob, Smith, Rocky, Sahai, Rohan, Ramchandani, Rohit, Huet, Romain, Carmichael, Rory, Zellers, Rowan, Chen, Roy, Chen, Ruby, Nigmatullin, Ruslan, Cheu, Ryan, Jain, Saachi, Altman, Sam, Schoenholz, Sam, Toizer, Sam, Miserendino, Samuel, Agarwal, Sandhini, Culver, Sara, Ethersmith, Scott, Gray, Scott, Grove, Sean, Metzger, Sean, Hermani, Shamez, Jain, Shantanu, Zhao, Shengjia, Wu, Sherwin, Jomoto, Shino, Wu, Shirong, Shuaiqi, Xia, Phene, Sonia, Papay, Spencer, Narayanan, Srinivas, Coffey, Steve, Lee, Steve, Hall, Stewart, Balaji, Suchir, Broda, Tal, Stramer, Tal, Xu, Tao, Gogineni, Tarun, Christianson, Taya, Sanders, Ted, Patwardhan, Tejal, Cunninghman, Thomas, Degry, Thomas, Dimson, Thomas, Raoux, Thomas, Shadwell, Thomas, Zheng, Tianhao, Underwood, Todd, Markov, Todor, Sherbakov, Toki, Rubin, Tom, Stasi, Tom, Kaftan, Tomer, Heywood, Tristan, Peterson, Troy, Walters, Tyce, Eloundou, Tyna, Qi, Valerie, Moeller, Veit, Monaco, Vinnie, Kuo, Vishal, Fomenko, Vlad, Chang, Wayne, Zheng, Weiyi, Zhou, Wenda, Manassra, Wesam, Sheu, Will, Zaremba, Wojciech, Patil, Yash, Qian, Yilei, Kim, Yongjik, Cheng, Youlong, Zhang, Yu, He, Yuchen, Zhang, Yuchen, Jin, Yujia, Dai, Yunxing, and Malkov, Yury
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Computers and Society, Computer Science - Machine Learning, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract: GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's trained end-to-end across text, vision, and audio, meaning all inputs and outputs are processed by the same neural network. GPT-4o can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50\% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models. In line with our commitment to building AI safely and consistent with our voluntary commitments to the White House, we are sharing the GPT-4o System Card, which includes our Preparedness Framework evaluations. In this System Card, we provide a detailed look at GPT-4o's capabilities, limitations, and safety evaluations across multiple categories, focusing on speech-to-speech while also evaluating text and image capabilities, and measures we've implemented to ensure the model is safe and aligned. We also include third-party assessments on dangerous capabilities, as well as discussion of potential societal impacts of GPT-4o's text and vision capabilities.
Published: 2024

3. From Lived Experiences to Social Activism: Latino Fraternity Brothers Critical Service to the Latinx Community

Author: Regina L. Suriel, James Martinez, Christian Bello Escobar, and Jamie L. Workman
Abstract: Colleges and universities are seeing growth of Latinx students actively engaged in Greek life. In this study, six Latino participants share their testimonios as members of different Chapters of a Latinx Greek Letter Organization (LGLO) nestled within Predominantly White Institutions located in the state of Georgia, USA. Informed by LatCrit theory, this qualitative study uses member's testimonios to shed light on their varied and sometimes politically charged and racist lived experiences. The researchers draw on these experiences to show how the LGLO supported these members' character and leadership development and their desire and commitment to critical service and socially just causes.
Published: 2024

4. A Novel Framework for the Automated Characterization of Gram-Stained Blood Culture Slides Using a Large-Scale Vision Transformer

Author: McMahon, Jack, Tomita, Naofumi, Tatishev, Elizabeth S., Workman, Adrienne A., Costales, Cristina R, Banaei, Niaz, Martin, Isabella W., and Hassanpour, Saeed
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract: This study introduces a new framework for the artificial intelligence-assisted characterization of Gram-stained whole-slide images (WSIs). As a test for the diagnosis of bloodstream infections, Gram stains provide critical early data to inform patient treatment. Rapid and reliable analysis of Gram stains has been shown to be positively associated with better clinical outcomes, underscoring the need for improved tools to automate Gram stain analysis. In this work, we developed a novel transformer-based model for Gram-stained WSI classification, which is more scalable to large datasets than previous convolutional neural network (CNN) -based methods as it does not require patch-level manual annotations. We also introduce a large Gram stain dataset from Dartmouth-Hitchcock Medical Center (Lebanon, New Hampshire, USA) to evaluate our model, exploring the classification of five major categories of Gram-stained WSIs: Gram-positive cocci in clusters, Gram-positive cocci in pairs/chains, Gram-positive rods, Gram-negative rods, and slides with no bacteria. Our model achieves a classification accuracy of 0.858 (95% CI: 0.805, 0.905) and an AUC of 0.952 (95% CI: 0.922, 0.976) using five-fold nested cross-validation on our 475-slide dataset, demonstrating the potential of large-scale transformer models for Gram stain classification. We further demonstrate the generalizability of our trained model, which achieves strong performance on external datasets without additional fine-tuning.
Published: 2024

5. Fair Railway Network Design

Author: He, Zixu, Botan, Sirin, Lang, Jérôme, Saffidine, Abdallah, Sikora, Florian, and Workman, Silas
Subjects: Computer Science - Social and Information Networks, Computer Science - Artificial Intelligence
Abstract: When designing a public transportation network in a country, one may want to minimise the sum of travel duration of all inhabitants. This corresponds to a purely utilitarian view and does not involve any fairness consideration, as the resulting network will typically benefit the capital city and/or large central cities while leaving some peripheral cities behind. On the other hand, a more egalitarian view will allow some people to travel between peripheral cities without having to go through a central city. We define a model, propose algorithms for computing solution networks, and report on experiments based on real data., Comment: 32 pages, 18 figures
Published: 2024

6. Mixed-View Panorama Synthesis using Geospatially Guided Diffusion

Author: Xiong, Zhexiao, Xing, Xin, Workman, Scott, Khanal, Subash, and Jacobs, Nathan
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: We introduce the task of mixed-view panorama synthesis, where the goal is to synthesize a novel panorama given a small set of input panoramas and a satellite image of the area. This contrasts with previous work which only uses input panoramas (same-view synthesis), or an input satellite image (cross-view synthesis). We argue that the mixed-view setting is the most natural to support panorama synthesis for arbitrary locations worldwide. A critical challenge is that the spatial coverage of panoramas is uneven, with few panoramas available in many regions of the world. We introduce an approach that utilizes diffusion-based modeling and an attention-based architecture for extracting information from all available input imagery. Experimental results demonstrate the effectiveness of our proposed method. In particular, our model can handle scenarios when the available panoramas are sparse or far from the location of the panorama we are attempting to synthesize.
Published: 2024

7. Global Data-Driven Determination of Baryon Transition Form Factors

Author: Wang, Yu-Fei, Döring, Michael, Hergenrather, Jackson, Mai, Maxim, Mart, Terry, Meißner, Ulf-G., Rönchen, Deborah, and Workman, Ronald
Subjects: Nuclear Theory, High Energy Physics - Phenomenology, Nuclear Experiment
Abstract: Hadronic resonances emerge from strong interactions encoding the dynamics of quarks and gluons. The structure of these resonances can be probed by virtual photons parameterized in transition form factors. In this study, twelve $N^*$ and $\Delta$ transition form factors at the pole are extracted from data with the center-of-mass energy from $\pi N$ threshold to $1.8\,{\rm GeV}$, and the photon virtuality $0\leq Q^2/{\rm GeV}^2\leq 8$. For the first time, these results are determined from a simultaneous analysis of more than one state, i.e., $\sim 10^5$ $\pi N$, $\eta N$, and $K\Lambda$ electroproduction data. In addition, about $ 5\cdot 10^4$ data in the hadronic sector as well as photoproduction serve as boundary conditions. For the $\Delta(1232)$ and $N(1440)$ states our results are in qualitative agreement with previous studies, while the transition form factors at the poles of some higher excited states are estimated for the first time. Realistic uncertainties are determined by further exploring the parameter space., Comment: Text: 6 pages, 4 figures. Supplemental Material: 3 pages, 2 figures
Published: 2024
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8. Single-channel, single-energy partial-wave analysis with continuity improved through minimal phase constraints

Author: Svarc, A. and Workman, R. L.
Subjects: Nuclear Theory
Abstract: Single-energy partial-wave analysis has often been applied as a way to fit data with minimal model dependence. However, remaining unconstrained, partial waves at neighboring energies will vary discontinuously because the overall amplitude phase cannot be determined through single-channel measurements. This problem can be mitigated through the use of a constraining penalty function based on an associated energy-dependent fit. However, the weight given to this constraint results in a biased fit to the data. In this paper, for the first time, we explore a constraining function which does not influence the fit to data. The constraint comes from the overall phase found in multi-channel fits which, in the present study, are the Bonn-Gatchina and J\"ulich-Bonn multi-channel analyses. The data are well reproduced and weighting of the penalty function does not influence the result. The method is applied to $K \Lambda$ photoproduction data and all observables can be maximally well reproduced. While the employed multi-channel analyses display very different multipole amplitudes, we show that the major difference between two sets of multipoles can be related to the different overall phases., Comment: 11 pages, 5 figures
Published: 2024

9. Social and genetic diversity in first farmers of central Europe

Author: Gelabert, Pere, Bickle, Penny, Hofmann, Daniela, Teschler-Nicola, Maria, Anders, Alexandra, Huang, Xin, Hämmerle, Michelle, Olalde, Iñigo, Fournier, Romain, Ringbauer, Harald, Akbari, Ali, Cheronet, Olivia, Lazaridis, Iosif, Broomandkhoshbacht, Nasreen, Fernandes, Daniel M., Buttinger, Katharina, Callan, Kim, Candilio, Francesca, Bravo Morante, Guillermo, Curtis, Elizabeth, Ferry, Matthew, Keating, Denise, Freilich, Suzanne, Kearns, Aisling, Harney, Éadaoin, Lawson, Ann Marie, Mandl, Kirsten, Michel, Megan, Oberreiter, Victoria, Zagorc, Brina, Oppenheimer, Jonas, Sawyer, Susanna, Schattke, Constanze, Özdoğan, Kadir Toykan, Qiu, Lijun, Workman, J. Noah, Zalzala, Fatma, Mallick, Swapan, Mah, Matthew, Micco, Adam, Pieler, Franz, Pavuk, Juraj, Šefčáková, Alena, Lazar, Catalin, Starović, Andrej, Djuric, Marija, Krznarić Škrivanko, Maja, Šlaus, Mario, Bedić, Željka, Novotny, Friederike, D. Szabó, László, Cserpák-Laczi, Orsolya, Hága, Tamara, Szolnoki, László, Hajdú, Zsigmond, Mirea, Pavel, Nagy, Emese Gyöngyvér, Virág, Zsuzsanna M., Horváth M., Attila, Horváth, László András, T. Biró, Katalin, Domboróczki, László, Szeniczey, Tamás, Jakucs, János, Szelekovszky, Márta, Zoltán, Farkas, Sztáncsuj, Sándor József, Tóth, Krisztián, Csengeri, Piroska, Pap, Ildikó, Patay, Róbert, Putica, Anđelka, Vasov, Branislav, Havasi, Bálint, Sebők, Katalin, Raczky, Pál, Lovász, Gabriella, Tvrdý, Zdeněk, Rohland, Nadin, Novak, Mario, Ruttkay, Matej, Krošláková, Maria, Bátora, Jozef, Paluch, Tibor, Borić, Dušan, Dani, János, Kuhlwilm, Martin, Palamara, Pier Francesco, Hajdu, Tamás, Pinhasi, Ron, and Reich, David
Published: 2024
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10. Safer and efficient base editing and prime editing via ribonucleoproteins delivered through optimized lipid-nanoparticle formulations

Author: Hołubowicz, Rafał, Du, Samuel W., Felgner, Jiin, Smidak, Roman, Choi, Elliot H., Palczewska, Grazyna, Menezes, Carolline Rodrigues, Dong, Zhiqian, Gao, Fangyuan, Medani, Omar, Yan, Alexander L., Hołubowicz, Maria W., Chen, Paul Z., Bassetto, Marco, Risaliti, Eleonora, Salom, David, Workman, J. Noah, Kiser, Philip D., Foik, Andrzej T., Lyon, David C., Newby, Gregory A., Liu, David R., Felgner, Philip L., and Palczewski, Krzysztof
Published: 2024
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11. Probabilistic Image-Driven Traffic Modeling via Remote Sensing

Author: Workman, Scott and Hadzic, Armin
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: This work addresses the task of modeling spatiotemporal traffic patterns directly from overhead imagery, which we refer to as image-driven traffic modeling. We extend this line of work and introduce a multi-modal, multi-task transformer-based segmentation architecture that can be used to create dense city-scale traffic models. Our approach includes a geo-temporal positional encoding module for integrating geo-temporal context and a probabilistic objective function for estimating traffic speeds that naturally models temporal variations. We evaluate our method extensively using the Dynamic Traffic Speeds (DTS) benchmark dataset and significantly improve the state-of-the-art. Finally, we introduce the DTS++ dataset to support mobility-related location adaptation experiments., Comment: European Conference on Computer Vision (ECCV) 2024
Published: 2024

12. Identifying Potential Inlets of Man in the Artificial Intelligence Development Process

Author: Workman, Deja and Dancy, Christopher L.
Subjects: Computer Science - Computers and Society, Computer Science - Artificial Intelligence, I.2.0, K.4.2
Abstract: In this paper we hope to identify how the typical or standard artificial intelligence development process encourages or facilitates the creation of racialized technologies. We begin by understanding Sylvia Wynter's definition of the biocentric Man genre and its exclusion of Blackness from humanness. We follow this with outlining what we consider to be the typical steps for developing an AI-based technology, which we have broken down into 6 stages: identifying a problem, development process and management tool selection, dataset development and data processing, model development, deployment and risk assessment, and integration and monitoring. The goal of this paper is to better understand how Wynter's biocentric Man is being represented and reinforced by the technologies we are producing in the AI lifecycle and by the lifecycle itself; we hope to identify ways in which the distinction of Blackness from the "ideal" human leads to perpetual punishment at the hands of these technologies. By deconstructing this development process, we can potentially identify ways in which humans in general have not been prioritized and how those affects are disproportionately affecting marginalized people. We hope to offer solutions that will encourage changes in the AI development cycle., Comment: Published in CSCW '23 Conference Proceedings. 7 pages, 1 figure
Published: 2024
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13. Prediction of Breast Cancer Recurrence Risk Using a Multi-Model Approach Integrating Whole Slide Imaging and Clinicopathologic Features

Author: Goyal, Manu, Marotti, Jonathan D., Workman, Adrienne A., Kuhn, Elaine P., Tooker, Graham M., Ramin, Seth K., Chamberlin, Mary D., diFlorio-Alexander, Roberta M., and Hassanpour, Saeed
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Breast cancer is the most common malignancy affecting women worldwide and is notable for its morphologic and biologic diversity, with varying risks of recurrence following treatment. The Oncotype DX Breast Recurrence Score test is an important predictive and prognostic genomic assay for estrogen receptor-positive breast cancer that guides therapeutic strategies; however, such tests can be expensive, delay care, and are not widely available. The aim of this study was to develop a multi-model approach integrating the analysis of whole slide images and clinicopathologic data to predict their associated breast cancer recurrence risks and categorize these patients into two risk groups according to the predicted score: low and high risk. The proposed novel methodology uses convolutional neural networks for feature extraction and vision transformers for contextual aggregation, complemented by a logistic regression model that analyzes clinicopathologic data for classification into two risk categories. This method was trained and tested on 993 hematoxylin and eosin-stained whole-slide images of breast cancers with corresponding clinicopathological features that had prior Oncotype DX testing. The model's performance was evaluated using an internal test set of 198 patients from Dartmouth Health and an external test set of 418 patients from the University of Chicago. The multi-model approach achieved an AUC of 0.92 (95 percent CI: 0.88-0.96) on the internal set and an AUC of 0.85 (95 percent CI: 0.79-0.90) on the external cohort. These results suggest that with further validation, the proposed methodology could provide an alternative to assist clinicians in personalizing treatment for breast cancer patients and potentially improving their outcomes., Comment: 16 pages, 4 figures and 4 tables
Published: 2024

14. A Comparison of Veterans with Problematic Opioid Use Identified through Natural Language Processing of Clinical Notes versus Using Diagnostic Codes

Author: Workman, Terri Elizabeth, Kupersmith, Joel, Ma, Phillip, Spevak, Christopher, Sandbrink, Friedhelm, and Zeng-Treitler, Yan Cheng Qing
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, J.3
Abstract: Background: Electronic health records (EHRs) are a data source for opioid research. Opioid use disorder is known to be under-coded as a diagnosis, yet problematic opioid use can be documented in clinical notes. Objectives: Our goals were 1) to identify problematic opioid use from a full range of clinical notes; and 2) to compare the characteristics of patients identified as having problematic opioid use, exclusively documented in clinical notes, to those having documented ICD opioid use disorder diagnostic codes. Materials and Methods: We developed and applied a natural language processing (NLP) tool to the clinical notes of a patient cohort (n=222,371) from two Veteran Affairs service regions to identify patients with problematic opioid use. We also used a set of ICD diagnostic codes to identify patients with opioid use disorder from the same cohort. We compared the demographic and clinical characteristics of patients identified only through NLP, to those of patients identified through ICD codes. Results: NLP exclusively identified 57,331 patients; 6,997 patients had positive ICD code identifications. Patients exclusively identified through NLP were more likely to be women. Those identified through ICD codes were more likely to be male, younger, have concurrent benzodiazepine prescriptions, more comorbidities, more care encounters, and less likely to be married. Patients in the NLP and ICD groups had substantially elevated comorbidity levels compared to patients not documented as experiencing problematic opioid use. Conclusions: NLP is a feasible approach for identifying problematic opioid use not otherwise recorded by ICD codes. Clinicians may be reluctant to code for opioid use disorder. It is therefore incumbent on the healthcare team to search for documentation of opioid concerns within clinical notes., Comment: 17 pages, 4 figures, 8 tables
Published: 2024

15. The Perceived Value of Using a Team Charter in Business Education

Author: Andrade, Maureen Snow, Westover, Jonathan, and Workman, Letty
Abstract: Business schools seek to prepare students for the workplace with employer-valued skills such as communication, teamwork, and application of knowledge. As such, a common practice for business and management educators is to involve students in collaborative team-based assignments and community projects. For example, to facilitate the development of teamwork skills, faculty members may have students create a team charter, which involves student teams identifying goals, roles, and norms. However, empirical evidence of the value of team charters is limited. This study examined student perceptions of team charters to determine if they played a role in effective teamwork or if other variables accounted for team success. The study entailed an analysis of a mid-semester team evaluation survey and an end-of-semester team charter survey. Findings indicated that overall, including the development and application of student charters in student group projects leads to several significant benefits and learning outcomes. However, the perceived usefulness of charters varies among students by level of experience and year in school.
Published: 2023

16. Team Charters in Business Education: The Importance of Perceived Level of Working Well Together

Author: Maureen Snow Andrade, Jonathan H. Westover, and Letty Workman
Abstract: Schools of business aim to help students develop employer-valued skills, which include communication, teamwork, critical thinking, and application of learning. This can be achieved through team assignments and community-based learning. Such approaches help students apply the concepts they are learning, collaborate with others, develop managerial skills, and solve real-life workplace issues. Teamwork is commonly thought to be enhanced when students establish a team charter outlining their goals, norms, and processes. Research on the value of team charters in business education, however, is limited. This study examined the role of team charters on student perceptions of working well together. Data was collected and analyzed from a mid-term team evaluation and a final team charter assessment. Findings indicated that perceived value of team charters differs across the year in school and tends to be higher for less experienced students. The provision of a structured project roadmap clarified team member roles, responsibilities, personal accountability, and team vision.
Published: 2023

17. A dynamic subpopulation of CRISPR–Cas overexpressers allows Streptococcus pyogenes to rapidly respond to phage

Author: Stoltzfus, Marie J., Workman, Rachael E., Keith, Nicholas C., and Modell, Joshua W.
Published: 2024
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18. Utensil Fading to Increase Appropriate Utensil Acceptance

Author: Kozlowski, Alison M., Clark, Racheal, Workman, Brittney, Chumney, Kathryn, and Birmingham, Taylor
Published: 2024
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19. Upper Semicontinuity of Index Plus Nullity for Minimal and CMC Hypersurfaces

Author: Workman, Myles
Subjects: Mathematics - Differential Geometry, Mathematics - Analysis of PDEs
Abstract: We consider a sequence of bubble converging minimal hypersurfaces, or H-CMC hypersurfaces, in compact Riemannian manifolds without boundary, of dimension 4, 5, 6 or 7, and prove upper semicontinuity of index plus nullity, for such a bubble converging sequence. This complements the previously known lower semicontinuity of index obtained by Buzano--Sharp, and Bourni--Sharp--Tinaglia. The strategy of our proof is to analyse a weighted eigenvalue problem along our sequence of hypersurfaces. This strategy is inspired by the recent work of Da Lio--Gianocca--Rivi\`{e}re. A key aspect of our proof is making use of a Lorentz--Sobolev inequality to study the behaviour of these weighted eigenfunctions on the neck regions along the sequence, as well as the index and nullity of our non-compact bubbles., Comment: Revised document, in which we have: corrected minor typos, added extra references, shortened preliminary section on bubble convergence, extended various statements on minimal hypersurfaces in Euclidean space to higher dimensions (under appropriate assumptions on their total curvature), and added a final section on Jacobi fields on the higher dimensional catenoid
Published: 2023

20. A mono-atomic orbital-based 1D topological crystalline insulator

Author: Liu, Gengming, Workman, Violet, Noh, Jiho, Ma, Yuhao, Hughes, Taylor L., Benalcazar, Wladimir A., and Bahl, Gaurav
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics
Abstract: Topological crystalline insulators (TCIs) are classified by topological invariants defined with respect to the crystalline symmetries of their gapped bulk. The bulk-boundary correspondence then links the topological properties of the bulk to robust observables on the edges, e.g., the existence of robust edge modes or fractional charge. In one dimension, TCIs protected by reflection symmetry have been realized in a variety of systems where each unit cell has spatially distributed degrees of freedom (SDoF). However, these realizations of TCIs face practical challenges stemming from the sensitivity of the resulting edge modes to variations in edge termination and to the local breaking of the protective spatial symmetries by inhomogeneity. Here we demonstrate topologically protected edge states in a mono-atomic, orbital-based TCI that mitigates both of these issues. By collapsing all SDoF within the unit cell to a singular point in space, we eliminate the ambiguity in unit cell definition and hence remove a prominent source of boundary termination variability. The topological observables are also more tolerant to disorder in the orbital energies. To validate this concept, we experimentally realize a lattice of mechanical resonators where each resonator acts as an "atom" that harbors two key orbital degrees of freedom having opposite reflection parity. Our measurements of this system provide direct visualization of the $sp$-hybridization between orbital modes that leads to a non-trivial band inversion in the bulk. Furthermore, as the spatial width of the resonators is tuned, one can drive a transition between a topological and trivial phase. In the future we expect our approach can be extended to realize orbital-based obstructed atomic insulators and TCIs in higher dimensions.
Published: 2023

21. Guideline concordant opioid therapy in Veterans receiving VA and community care

Author: Ma, Phillip, Cheng, Yan, Goulet, Joseph L., Sandbrink, Friedhelm, Brandt, Cynthia, Spevak, Chris, Kean, Jacob T., Becker, William, Libin, Alexander, Shara, Nawar, Sheriff, Helen M, Houston, James S., Butler, Jorie, Workman, Elizabeth T., Agrawal, Rajeev M, Kupersmith, Joel, and Zeng-Treitler, Qing
Published: 2024
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22. A multi-model approach integrating whole-slide imaging and clinicopathologic features to predict breast cancer recurrence risk

Author: Goyal, Manu, Marotti, Jonathan D., Workman, Adrienne A., Tooker, Graham M., Ramin, Seth K., Kuhn, Elaine P., Chamberlin, Mary D., diFlorio-Alexander, Roberta M., and Hassanpour, Saeed
Published: 2024
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23. Clonal background and routes of plasmid transmission underlie antimicrobial resistance features of bloodstream Klebsiella pneumoniae

Author: Ikhimiukor, Odion O., Zac Soligno, Nicole I., Akintayo, Ifeoluwa J., Marcovici, Michael M., Souza, Stephanie S. R., Workman, Adrienne, Martin, Isabella W., and Andam, Cheryl P.
Published: 2024
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24. Author Correction: Aplp1 interacts with Lag3 to facilitate transmission of pathologic α-synuclein

Author: Mao, Xiaobo, Gu, Hao, Kim, Donghoon, Kimura, Yasuyoshi, Wang, Ning, Xu, Enquan, Kumbhar, Ramhari, Ming, Xiaotian, Wang, Haibo, Chen, Chan, Zhang, Shengnan, Jia, Chunyu, Liu, Yuqing, Bian, Hetao, Karuppagounder, Senthilkumar S., Akkentli, Fatih, Chen, Qi, Jia, Longgang, Hwang, Heehong, Lee, Su Hyun, Ke, Xiyu, Chang, Michael, Li, Amanda, Yang, Jun, Rastegar, Cyrus, Sriparna, Manjari, Ge, Preston, Brahmachari, Saurav, Kim, Sangjune, Zhang, Shu, Shimoda, Yasushi, Saar, Martina, Liu, Haiqing, Kweon, Sin Ho, Ying, Mingyao, Workman, Creg J., Vignali, Dario A. A., Muller, Ulrike C., Liu, Cong, Ko, Han Seok, Dawson, Valina L., and Dawson, Ted M.
Published: 2024
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25. Inhibition and reversal of a TGF-β1 induced myofibroblast phenotype by adipose tissue-derived paracrine factors

Author: Higginbotham, S., Workman, V. L., Giblin, A-V., Green, N. H., Lambert, D. W., and Hearnden, V.
Published: 2024
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26. Aplp1 interacts with Lag3 to facilitate transmission of pathologic α-synuclein

Author: Mao, Xiaobo, Gu, Hao, Kim, Donghoon, Kimura, Yasuyoshi, Wang, Ning, Xu, Enquan, Kumbhar, Ramhari, Ming, Xiaotian, Wang, Haibo, Chen, Chan, Zhang, Shengnan, Jia, Chunyu, Liu, Yuqing, Bian, Hetao, Karuppagounder, Senthilkumar S., Akkentli, Fatih, Chen, Qi, Jia, Longgang, Hwang, Heehong, Lee, Su Hyun, Ke, Xiyu, Chang, Michael, Li, Amanda, Yang, Jun, Rastegar, Cyrus, Sriparna, Manjari, Ge, Preston, Brahmachari, Saurav, Kim, Sangjune, Zhang, Shu, Shimoda, Yasushi, Saar, Martina, Liu, Haiqing, Kweon, Sin Ho, Ying, Mingyao, Workman, Creg J., Vignali, Dario A. A., Muller, Ulrike C., Liu, Cong, Ko, Han Seok, Dawson, Valina L., and Dawson, Ted M.
Published: 2024
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27. Art therapy masks reflect emotional changes in military personnel with PTSS

Author: Estrada Gonzalez, V., Meletaki, V., Walker, M., Payano Sosa, J., Stamper, A., Srikanchana, R., King, J. L., Scott, K., Cardillo, E. R., Rhodes, C. Sours, Christensen, A. P., Darda, K. M., Workman, C. I., and Chatterjee, A.
Published: 2024
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28. Guideline concordant opioid therapy in Veterans receiving VA and community care

Author: Phillip Ma, Yan Cheng, Joseph L. Goulet, Friedhelm Sandbrink, Cynthia Brandt, Chris Spevak, Jacob T. Kean, William Becker, Alexander Libin, Nawar Shara, Helen M Sheriff, James S. Houston, Jorie Butler, Elizabeth T. Workman, Rajeev M Agrawal, Joel Kupersmith, and Qing Zeng-Treitler
Subjects: Opioid therapy disorder, Concordant care, Drug adherence, Mono vs dual-system, Public aspects of medicine, RA1-1270
Abstract: Abstract Guideline concordant opioid therapy is a key part of the concerted effort to address the opioid crisis in the United States. The study aimed to compare the rates of guideline concordant care between veterans who solely used VA services (mono users) and veterans who used both VA services and community care (dual-system users). We used electronic health record data from the Washington DC and Baltimore VA Medical Centers from 2015 to 2019. We provided descriptive statistics as well as generalized estimating equations models to find associations between mono vs. dual-system users and each guideline outcome, controlling for demographic factors and comorbid conditions. The study found that overall rates of guideline concordant care were high in both mono and dual-system users with over 90% adherence rates for the majority of recommendations. However, there were variations in adherence to specific guidelines, with urine drug screening at initiation being the least commonly followed recommendation (8.9% of mono-user opioid initiators and 11.2% of dual-user initiators). This study also found that there was no consistent pattern of higher guideline adherence in mono vs. dual-system users but did show that through the course of this study (2015–2019) overall rates of guideline concordance increased. Future research will explore additional guideline recommendations and potential coordination issues among dual-system users.
Published: 2024
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29. A multi-model approach integrating whole-slide imaging and clinicopathologic features to predict breast cancer recurrence risk

Author: Manu Goyal, Jonathan D. Marotti, Adrienne A. Workman, Graham M. Tooker, Seth K. Ramin, Elaine P. Kuhn, Mary D. Chamberlin, Roberta M. diFlorio-Alexander, and Saeed Hassanpour
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Breast cancer is the most common malignancy affecting women worldwide and is notable for its morphologic and biologic diversity, with varying risks of recurrence following treatment. The Oncotype DX Breast Recurrence Score test is an important predictive and prognostic genomic assay for estrogen receptor positive/HER2 negative breast cancer that guides therapeutic strategies; however, such tests can be expensive, delay care, and are not widely available. The aim of this study was to develop a multi-model approach integrating the analysis of whole-slide images and clinicopathologic data to predict their associated breast cancer recurrence risks and categorize these patients into two risk groups according to the predicted score: low-risk and high-risk. The proposed novel methodology uses convolutional neural networks for feature extraction and vision transformers for contextual aggregation, complemented by a logistic regression model that analyzes clinicopathologic data for classification into two risk categories. This method was trained and tested on 956 hematoxylin and eosin-stained whole-slide images of 950 ER+/HER2− breast cancer patients with corresponding clinicopathological features that had prior Oncotype DX testing. The model’s performance was evaluated using an internal test set of 192 patients from Dartmouth Health and an external test set of 405 patients from the University of Chicago. The multi-model approach achieved an AUC of 0.91 (95% CI: 0.87–0.95) on the internal set and an AUC of 0.84 (95% CI: 0.78–0.89) on the external cohort for predicting low- and high-breast cancer recurrence risk categories based on the Oncotype DX recurrence score. With further validation, the proposed methodology could provide an alternative to assist clinicians in personalizing treatment for breast cancer patients and potentially improving their outcomes.
Published: 2024
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30. Discipline Disproportionality in Rural Schools in the South

Author: Workman, Julie and Wake, Donna
Abstract: This study uses an explanatory sequential mixed-methods approach to examine principals'responses to their schools' disproportionate discipline data in five schools located in the ruralsoutheastern United States. Semi-structured interviews were analyzed for principals' insight intotheir school discipline data. Results indicated that Black students were being disciplined at higherrates than white students in all five schools with principals sharing varied responses in discussingperceptions of causality. Principals attributed disproportionate discipline to a cultural mismatchbetween teachers and students, followed by student trauma and mental health issues.Recommendations are made for principal action and preparation.
Published: 2022

31. Exploring the Experiences of Male Intercollegiate Soccer Coaches Who Are People of Color

Author: Patrice Parris, Jamie Workman, James Archibald, and Eugene Asola
Abstract: The purpose of this study was to explore and discuss the lived experiences and stories of people of color male intercollegiate soccer coaches, and to make meaning of their experiences to better understand why there are a lack of people of color male coaches in the NCAA soccer community. Critical race theory served as the theoretical framework. Through the use of narrative inquiry, the researchers interviewed people of color male soccer coaches in the NCAA. The researchers analyzed, categorized, and coded into themes using procedures for conducting and analyzing narrative research. Several themes emerged from interviews with six people of color college male soccer coaches. In this article, the authors discuss two major themes, relationships and race, and provides implications for intercollegiate coaches and administrators as well as directions for future research.
Published: 2024
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32. Structure Studies of $^{13}\text{Be}$ from the $^{12}$Be(d,p) reaction in inverse kinematics on a solid deuteron target

Author: Kovoor, J., Jones, K. L., Hooker, J., Vostinar, M., Kanungo, R., Pain, S. D., Alcorta, M., Allen, J., Andreoiu, C., Atar, L., Bardayan, D. W., Bhattacharjee, S. S., Blankstein, D., Burbadge, C., Burcher, S., Catford, W. N., Cha, S., Chae, K., Connolly, D., Davids, B., Esker, N. E., Garcia, F. H., Gillespie, S., Ghimire, R., Gula, A., Hackman, G., Hallam, S., Hellmich, M., Henderson, J., Holl, M., Jassal, P., King, S., Knight, T., Kruecken, R., Lepailleur, A., Liang, J., Morrison, L., O'Malley, P. D., Pereira-Lopez, X., Psaltis, A., Radich, A., Refsgaard, J., Shotter, A. C., Williams, M., and Workman, O.
Subjects: Nuclear Experiment
Abstract: The low-lying structure of $^{13}$Be has remained an enigma for decades. Despite numerous experimental and theoretical studies, large inconsistencies remain. Being both unbound, and one neutron away from $^{14}$Be, the heaviest bound beryllium nucleus, $^{13}$Be is difficult to study through simple reactions with weak radioactive ion beams or more complex reactions with stable-ion beams. Here, we present the results of a study using the $^{12}$Be(d,p)$^{13}$Be reaction in inverse kinematics using a 9.5~MeV per nucleon $^{12}$Be beam from the ISAC-II facility. The solid deuteron target of IRIS was used to achieve an increased areal thickness compared to conventional deuterated polyethylene targets. The Q-value spectrum below -4.4~MeV was analyzed using a Bayesian method with GEANT4 simulations. A three-point angular distribution with the same Q-value gate was fit with a mixture of $s$- and $p$-wave, $s$- and $d$-wave, or pure $p$-wave transfer. The Q-value spectrum was also compared with GEANT simulations obtained using the energies and widths of states reported in four previous works. It was found that our results are incompatible with works that revealed a wide $5/2^+$ resonance but shows better agreement with ones that reported a narrower width., Comment: 10 pages, 5 figures
Published: 2023
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33. Extended SAID Partial-Wave Analysis of Pion Photoproduction

Author: Briscoe, William J., Schmidt, Axel, Strakovsky, Igor, Workman, Ron L., and Svarc, Alfred
Subjects: High Energy Physics - Phenomenology, High Energy Physics - Experiment, Nuclear Experiment, Nuclear Theory
Abstract: A unified Chew-Mandelstam description of single-pion photoproduction data, together with pion- and eta-hadroproduction data, has been extended to include measurements carried out over the last decade. We consider photo-decay amplitudes evaluated at the pole with particular emphasis on ng couplings and the influence of weighting on our fits. Both energy-dependent and single-energy analysis (energy-binned data) are considered., Comment: 30 pages, 18 figures, and 14 tables
Published: 2023

34. Inclusion of $K\Lambda$ electroproduction data in a coupled channel analysis

Author: Mai, M., Hergenrather, J., Döring, M., Mart, T., Meißner, Ulf-G., Rönchen, D., and Workman, R.
Subjects: Nuclear Theory, High Energy Physics - Phenomenology, Nuclear Experiment
Abstract: Exclusive electroproduction reactions provide an access to the structure of excited baryons. To extract electroproduction multipoles encoding this information, the J\"ulich-Bonn-Washington (JBW) analysis framework is extended to the analysis of differential cross sections in $K\Lambda$ electroproduction. This update enlarges the scope of previous coupled-channel analyses of pions and eta mesons, with photoproduction reactions as boundary condition in all analyzed electroproduction reactions. Polarization observables are predicted and compared to recent CLAS data. The comparison shows the relevance of these data to pin down baryon properties., Comment: 21 pages, 13 figures
Published: 2023

35. Medieval DNA from Soqotra points to Eurasian origins of an isolated population at the crossroads of Africa and Arabia

Author: Sirak, Kendra, Jansen Van Rensburg, Julian, Brielle, Esther, Chen, Bowen, Lazaridis, Iosif, Ringbauer, Harald, Mah, Matthew, Mallick, Swapan, Micco, Adam, Rohland, Nadin, Callan, Kimberly, Curtis, Elizabeth, Kearns, Aisling, Lawson, Ann Marie, Workman, J. Noah, Zalzala, Fatma, Ahmed Al-Orqbi, Ahmed Saeed, Ahmed Salem, Esmail Mohammed, Salem Hasan, Ali Mohammed, Britton, Daniel Charles, and Reich, David
Published: 2024
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36. The afterglow of GW170817 from every angle: Prospects for detecting the afterglows of binary neutron star mergers

Author: Morsony, Brian James, Santos, Ryan De Los, Hernandez, Rubin, Bustamante, Joshua, Yassuiae, Brandon, Astorga, German, Parra, Juan, and Workman, Jared C.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: To date GW170817, produced by a binary neutron star (BNS) merger, is the only gravitational wave event with an electromagnetic (EM) counterpart. It was associated with a prompt short gamma-ray burst (GRB), an optical kilonova, and the afterglow of a structured, off-axis relativistic jet. We model the prospects for future mergers discovered in gravitational waves to produce detectable afterglows. Using a model fit to GW170817, we assume all BNS mergers produce jets with the same parameters, and model the afterglow luminosity for a full distribution of observer angles, ISM densities, and distances. We find that in the LIGO/Virgo/KAGRA O4 run, 30% - 45% of BNS mergers with a well-localized counterpart will have an afterglow detectable with current instrumentation in the X-ray, radio and optical. Without a previously detected counterpart, 10% - 15% will have an afterglow detectable by wide-area radio and optical surveys, compared to only about 5% - 12% of events expected to have bright (on-axis) gamma-ray emission. Most afterglows that are detected will be from off-axis jets. Further in the future, in the A+ era (O5), 40% - 50% of mergers will have afterglows detectable with next-generation X-ray and radio instruments. Future wide-area radio survey instruments, particularly DSA-2000, could detect 40% of afterglows, even without a kilonova counterpart. Finding and monitoring these afterglows will provide valuable insight into the structure and diversity of relativistic jets, the rate at which mergers produce jets, and constrain the angle of the mergers relative to our line of sight., Comment: Accepted by MNRAS
Published: 2023

37. Measurement of the helicity asymmetry $\mathbb{E}$ for the $\vec{\gamma}\vec{p} \to p \pi^0$ reaction in the resonance region

Author: Chan, K., Zachariou, N., Bashkanov, M., Briscoe, W. J., Fegan, S., Kashevarov, V. L., Nikonov, K., Sarantsev, A., Schmidt, A., Strakovsky, I. I., Watts, D. P., and Workman, R. L.
Subjects: Nuclear Experiment
Abstract: The double-spin-polarization observable $\mathbb{E}$ for $\vec{\gamma}\vec{p}\to p\pi^0$ has been measured with the CEBAF Large Acceptance Spectrometer (CLAS) at photon beam energies $E_\gamma$ from 0.367 to $2.173~\mathrm{GeV}$ (corresponding to center-of-mass energies from 1.240 to $2.200~\mathrm{GeV}$) for pion center-of-mass angles, $\cos\theta_{\pi^0}^{c.m.}$, between -0.86 and 0.82. These new CLAS measurements cover a broader energy range and have smaller uncertainties compared to previous CBELSA data and provide an important independent check on systematics. These measurements are compared to predictions as well as new global fits from The George Washington University, Mainz, and Bonn-Gatchina groups. Their inclusion in multipole analyses will refine our understanding of the single-pion production contribution to the Gerasimov-Drell-Hearn sum rule and improve the determination of resonance properties., Comment: 11 pages, 5 figures
Published: 2023

38. Is the LHCb $P_c(4312)^+$ plausible in the GlueX $\gamma p\to J/\psi p$ total cross sections ?

Author: Strakovsky, Igor, Briscoe, William J., Chudakov, Eugene, Larin, Ilya, Pentchev, Lubomir, Schmidt, Axel, and Workman, Ronald L.
Subjects: High Energy Physics - Phenomenology, High Energy Physics - Experiment, Nuclear Experiment, Nuclear Theory
Abstract: New high-statistics total cross section data for $\gamma p\to J/\psi p$ from the GLUonic EXcitation (GlueX) experiment are fitted in a search for the exotic $P_c(4312)^+$ state observed by the Large Hadron Collider beauty (LHCb) collaboration. The integrated luminosity of this GlueX experiment was about $320~\mathrm{pb^{-1}}$. The fits show that destructive interference involving an $S$-wave resonance and associated non-resonance background produces a sharp dip structure about $75~\mathrm{MeV}$ below the LHCb mass, in the same location as a similar structure is seen in the data. Limitations of the employed model and the need for improved statistics are discussed., Comment: 4 pages, 3 figures, 2 tables
Published: 2023

39. The James Webb Space Telescope Mission

Author: Gardner, Jonathan P., Mather, John C., Abbott, Randy, Abell, James S., Abernathy, Mark, Abney, Faith E., Abraham, John G., Abraham, Roberto, Abul-Huda, Yasin M., Acton, Scott, Adams, Cynthia K., Adams, Evan, Adler, David S., Adriaensen, Maarten, Aguilar, Jonathan Albert, Ahmed, Mansoor, Ahmed, Nasif S., Ahmed, Tanjira, Albat, Rüdeger, Albert, Loïc, Alberts, Stacey, Aldridge, David, Allen, Mary Marsha, Allen, Shaune S., Altenburg, Martin, Altunc, Serhat, Alvarez, Jose Lorenzo, Álvarez-Márquez, Javier, de Oliveira, Catarina Alves, Ambrose, Leslie L., Anandakrishnan, Satya M., Andersen, Gregory C., Anderson, Harry James, Anderson, Jay, Anderson, Kristen, Anderson, Sara M., Aprea, Julio, Archer, Benita J., Arenberg, Jonathan W., Argyriou, Ioannis, Arribas, Santiago, Artigau, Étienne, Arvai, Amanda Rose, Atcheson, Paul, Atkinson, Charles B., Averbukh, Jesse, Aymergen, Cagatay, Bacinski, John J., Baggett, Wayne E., Bagnasco, Giorgio, Baker, Lynn L., Balzano, Vicki Ann, Banks, Kimberly A., Baran, David A., Barker, Elizabeth A., Barrett, Larry K., Barringer, Bruce O., Barto, Allison, Bast, William, Baudoz, Pierre, Baum, Stefi, Beatty, Thomas G., Beaulieu, Mathilde, Bechtold, Kathryn, Beck, Tracy, Beddard, Megan M., Beichman, Charles, Bellagama, Larry, Bely, Pierre, Berger, Timothy W., Bergeron, Louis E., Darveau-Bernier, Antoine, Bertch, Maria D., Beskow, Charlotte, Betz, Laura E., Biagetti, Carl P., Birkmann, Stephan, Bjorklund, Kurt F., Blackwood, James D., Blazek, Ronald Paul, Blossfeld, Stephen, Bluth, Marcel, Boccaletti, Anthony, Boegner Jr., Martin E., Bohlin, Ralph C., Boia, John Joseph, Böker, Torsten, Bonaventura, N., Bond, Nicholas A., Bosley, Kari Ann, Boucarut, Rene A., Bouchet, Patrice, Bouwman, Jeroen, Bower, Gary, Bowers, Ariel S., Bowers, Charles W., Boyce, Leslye A., Boyer, Christine T., Boyer, Martha L., Boyer, Michael, Boyer, Robert, Bradley, Larry D., Brady, Gregory R., Brandl, Bernhard R., Brannen, Judith L., Breda, David, Bremmer, Harold G., Brennan, David, Bresnahan, Pamela A., Bright, Stacey N., Broiles, Brian J., Bromenschenkel, Asa, Brooks, Brian H., Brooks, Keira J., Brown, Bob, Brown, Bruce, Brown, Thomas M., Bruce, Barry W., Bryson, Jonathan G., Bujanda, Edwin D., Bullock, Blake M., Bunker, A. J., Bureo, Rafael, Burt, Irving J., Bush, James Aaron, Bushouse, Howard A., Bussman, Marie C., Cabaud, Olivier, Cale, Steven, Calhoon, Charles D., Calvani, Humberto, Canipe, Alicia M., Caputo, Francis M., Cara, Mihai, Carey, Larkin, Case, Michael Eli, Cesari, Thaddeus, Cetorelli, Lee D., Chance, Don R., Chandler, Lynn, Chaney, Dave, Chapman, George N., Charlot, S., Chayer, Pierre, Cheezum, Jeffrey I., Chen, Bin, Chen, Christine H., Cherinka, Brian, Chichester, Sarah C., Chilton, Zachary S., Chittiraibalan, Dharini, Clampin, Mark, Clark, Charles R., Clark, Kerry W., Clark, Stephanie M., Claybrooks, Edward E., Cleveland, Keith A., Cohen, Andrew L., Cohen, Lester M., Colón, Knicole D., Coleman, Benee L., Colina, Luis, Comber, Brian J., Comeau, Thomas M., Comer, Thomas, Reis, Alain Conde, Connolly, Dennis C., Conroy, Kyle E., Contos, Adam R., Contreras, James, Cook, Neil J., Cooper, James L., Cooper, Rachel Aviva, Correia, Michael F., Correnti, Matteo, Cossou, Christophe, Costanza, Brian F., Coulais, Alain, Cox, Colin R., Coyle, Ray T., Cracraft, Misty M., Noriega-Crespo, Alberto, Crew, Keith A., Curtis, Gary J., Cusveller, Bianca, Maciel, Cleyciane Da Costa, Dailey, Christopher T., Daugeron, Frédéric, Davidson, Greg S., Davies, James E., Davis, Katherine Anne, Davis, Michael S., Day, Ratna, de Chambure, Daniel, de Jong, Pauline, De Marchi, Guido, Dean, Bruce H., Decker, John E., Delisa, Amy S., Dell, Lawrence C., Dellagatta, Gail, Dembinska, Franciszka, Demosthenes, Sandor, Dencheva, Nadezhda M., Deneu, Philippe, DePriest, William W., Deschenes, Jeremy, Dethienne, Nathalie, Detre, Örs Hunor, Diaz, Rosa Izela, Dicken, Daniel, DiFelice, Audrey S., Dillman, Matthew, Disharoon, Maureen O., van Dishoeck, Ewine F., Dixon, William V., Doggett, Jesse B., Dominguez, Keisha L., Donaldson, Thomas S., Doria-Warner, Cristina M., Santos, Tony Dos, Doty, Heather, Douglas Jr., Robert E., Doyon, René, Dressler, Alan, Driggers, Jennifer, Driggers, Phillip A., Dunn, Jamie L., DuPrie, Kimberly C., Dupuis, Jean, Durning, John, Dutta, Sanghamitra B., Earl, Nicholas M., Eccleston, Paul, Ecobichon, Pascal, Egami, Eiichi, Ehrenwinkler, Ralf, Eisenhamer, Jonathan D., Eisenhower, Michael, Eisenstein, Daniel J., Hamel, Zaky El, Elie, Michelle L., Elliott, James, Elliott, Kyle Wesley, Engesser, Michael, Espinoza, Néstor, Etienne, Odessa, Etxaluze, Mireya, Evans, Leah, Fabreguettes, Luce, Falcolini, Massimo, Falini, Patrick R., Fatig, Curtis, Feeney, Matthew, Feinberg, Lee D., Fels, Raymond, Ferdous, Nazma, Ferguson, Henry C., Ferrarese, Laura, Ferreira, Marie-Héléne, Ferruit, Pierre, Ferry, Malcolm, Filippazzo, Joseph Charles, Firre, Daniel, Fix, Mees, Flagey, Nicolas, Flanagan, Kathryn A., Fleming, Scott W., Florian, Michael, Flynn, James R., Foiadelli, Luca, Fontaine, Mark R., Fontanella, Erin Marie, Forshay, Peter Randolph, Fortner, Elizabeth A., Fox, Ori D., Framarini, Alexandro P., Francisco, John I., Franck, Randy, Franx, Marijn, Franz, David E., Friedman, Scott D., Friend, Katheryn E., Frost, James R., Fu, Henry, Fullerton, Alexander W., Gaillard, Lionel, Galkin, Sergey, Gallagher, Ben, Galyer, Anthony D., Marín, Macarena García, Gardner, Lisa E., Garland, Dennis, Garrett, Bruce Albert, Gasman, Danny, Gáspár, András, Gastaud, René, Gaudreau, Daniel, Gauthier, Peter Timothy, Geers, Vincent, Geithner, Paul H., Gennaro, Mario, Gerber, John, Gereau, John C., Giampaoli, Robert, Giardino, Giovanna, Gibbons, Paul C., Gilbert, Karolina, Gilman, Larry, Girard, Julien H., Giuliano, Mark E., Gkountis, Konstantinos, Glasse, Alistair, Glassmire, Kirk Zachary, Glauser, Adrian Michael, Glazer, Stuart D., Goldberg, Joshua, Golimowski, David A., Gonzaga, Shireen P., Gordon, Karl D., Gordon, Shawn J., Goudfrooij, Paul, Gough, Michael J., Graham, Adrian J., Grau, Christopher M., Green, Joel David, Greene, Gretchen R., Greene, Thomas P., Greenfield, Perry E., Greenhouse, Matthew A., Greve, Thomas R., Greville, Edgar M., Grimaldi, Stefano, Groe, Frank E., Groebner, Andrew, Grumm, David M., Grundy, Timothy, Güdel, Manuel, Guillard, Pierre, Guldalian, John, Gunn, Christopher A., Gurule, Anthony, Gutman, Irvin Meyer, Guy, Paul D., Guyot, Benjamin, Hack, Warren J., Haderlein, Peter, Hagan, James B., Hagedorn, Andria, Hainline, Kevin, Haley, Craig, Hami, Maryam, Hamilton, Forrest Clifford, Hammann, Jeffrey, Hammel, Heidi B., Hanley, Christopher J., Hansen, Carl August, Hardy, Bruce, Harnisch, Bernd, Harr, Michael Hunter, Harris, Pamela, Hart, Jessica Ann, Hartig, George F., Hasan, Hashima, Hashim, Kathleen Marie, Hashimoto, Ryan, Haskins, Sujee J., Hawkins, Robert Edward, Hayden, Brian, Hayden, William L., Healy, Mike, Hecht, Karen, Heeg, Vince J., Hejal, Reem, Helm, Kristopher A., Hengemihle, Nicholas J., Henning, Thomas, Henry, Alaina, Henry, Ronald L., Henshaw, Katherine, Hernandez, Scarlin, Herrington, Donald C., Heske, Astrid, Hesman, Brigette Emily, Hickey, David L., Hilbert, Bryan N., Hines, Dean C., Hinz, Michael R., Hirsch, Michael, Hitcho, Robert S., Hodapp, Klaus, Hodge, Philip E., Hoffman, Melissa, Holfeltz, Sherie T., Holler, Bryan Jason, Hoppa, Jennifer Rose, Horner, Scott, Howard, Joseph M., Howard, Richard J., Huber, Jean M., Hunkeler, Joseph S., Hunter, Alexander, Hunter, David Gavin, Hurd, Spencer W., Hurst, Brendan J., Hutchings, John B., Hylan, Jason E., Ignat, Luminita Ilinca, Illingworth, Garth, Irish, Sandra M., Isaacs III, John C., Jackson Jr., Wallace C., Jaffe, Daniel T., Jahic, Jasmin, Jahromi, Amir, Jakobsen, Peter, James, Bryan, James, John C., James, LeAndrea Rae, Jamieson, William Brian, Jandra, Raymond D., Jayawardhana, Ray, Jedrzejewski, Robert, Jeffers, Basil S., Jensen, Peter, Joanne, Egges, Johns, Alan T., Johnson, Carl A., Johnson, Eric L., Johnson, Patricia, Johnson, Phillip Stephen, Johnson, Thomas K., Johnson, Timothy W., Johnstone, Doug, Jollet, Delphine, Jones, Danny P., Jones, Gregory S., Jones, Olivia C., Jones, Ronald A., Jones, Vicki, Jordan, Ian J., Jordan, Margaret E., Jue, Reginald, Jurkowski, Mark H., Justis, Grant, Justtanont, Kay, Kaleida, Catherine C., Kalirai, Jason S., Kalmanson, Phillip Cabrales, Kaltenegger, Lisa, Kammerer, Jens, Kan, Samuel K., Kanarek, Graham Childs, Kao, Shaw-Hong, Karakla, Diane M., Karl, Hermann, Kassin, Susan A., Kauffman, David D., Kavanagh, Patrick, Kelley, Leigh L., Kelly, Douglas M., Kendrew, Sarah, Kennedy, Herbert V., Kenny, Deborah A., Keski-Kuha, Ritva A., Keyes, Charles D., Khan, Ali, Kidwell, Richard C., Kimble, Randy A., King, James S., King, Richard C., Kinzel, Wayne M., Kirk, Jeffrey R., Kirkpatrick, Marc E., Klaassen, Pamela, Klingemann, Lana, Klintworth, Paul U., Knapp, Bryan Adam, Knight, Scott, Knollenberg, Perry J., Knutsen, Daniel Mark, Koehler, Robert, Koekemoer, Anton M., Kofler, Earl T., Kontson, Vicki L., Kovacs, Aiden Rose, Kozhurina-Platais, Vera, Krause, Oliver, Kriss, Gerard A., Krist, John, Kristoffersen, Monica R., Krogel, Claudia, Krueger, Anthony P., Kulp, Bernard A., Kumari, Nimisha, Kwan, Sandy W., Kyprianou, Mark, Labador, Aurora Gadiano, Labiano, Álvaro, Lafrenière, David, Lagage, Pierre-Olivier, Laidler, Victoria G., Laine, Benoit, Laird, Simon, Lajoie, Charles-Philippe, Lallo, Matthew D., Lam, May Yen, LaMassa, Stephanie Marie, Lambros, Scott D., Lampenfield, Richard Joseph, Lander, Matthew Ed, Langston, James Hutton, Larson, Kirsten, Larson, Melora, LaVerghetta, Robert Joseph, Law, David R., Lawrence, Jon F., Lee, David W., Lee, Janice, Lee, Yat-Ning Paul, Leisenring, Jarron, Leveille, Michael Dunlap, Levenson, Nancy A., Levi, Joshua S., Levine, Marie B., Lewis, Dan, Lewis, Jake, Lewis, Nikole, Libralato, Mattia, Lidon, Norbert, Liebrecht, Paula Louisa, Lightsey, Paul, Lilly, Simon, Lim, Frederick C., Lim, Pey Lian, Ling, Sai-Kwong, Link, Lisa J., Link, Miranda Nicole, Lipinski, Jamie L., Liu, XiaoLi, Lo, Amy S., Lobmeyer, Lynette, Logue, Ryan M., Long, Chris A., Long, Douglas R., Long, Ilana D., Long, Knox S., López-Caniego, Marcos, Lotz, Jennifer M., Love-Pruitt, Jennifer M., Lubskiy, Michael, Luers, Edward B., Luetgens, Robert A., Luevano, Annetta J., Lui, Sarah Marie G. Flores, Lund III, James M., Lundquist, Ray A., Lunine, Jonathan, Lützgendorf, Nora, Lynch, Richard J., MacDonald, Alex J., MacDonald, Kenneth, Macias, Matthew J., Macklis, Keith I., Maghami, Peiman, Maharaja, Rishabh Y., Maiolino, Roberto, Makrygiannis, Konstantinos G., Malla, Sunita Giri, Malumuth, Eliot M., Manjavacas, Elena, Marini, Andrea, Marrione, Amanda, Marston, Anthony, Martel, André R, Martin, Didier, Martin, Peter G., Martinez, Kristin L., Maschmann, Marc, Masci, Gregory L., Masetti, Margaret E., Maszkiewicz, Michael, Matthews, Gary, Matuskey, Jacob E., McBrayer, Glen A., McCarthy, Donald W., McCaughrean, Mark J., McClare, Leslie A., McClare, Michael D., McCloskey, John C., McClurg, Taylore D., McCoy, Martin, McElwain, Michael W., McGregor, Roy D., McGuffey, Douglas B., McKay, Andrew G., McKenzie, William K., McLean, Brian, McMaster, Matthew, McNeil, Warren, De Meester, Wim, Mehalick, Kimberly L., Meixner, Margaret, Meléndez, Marcio, Menzel, Michael P., Menzel, Michael T., Merz, Matthew, Mesterharm, David D., Meyer, Michael R., Meyett, Michele L., Meza, Luis E., Midwinter, Calvin, Milam, Stefanie N., Miller, Jay Todd, Miller, William C., Miskey, Cherie L., Misselt, Karl, Mitchell, Eileen P., Mohan, Martin, Montoya, Emily E., Moran, Michael J., Morishita, Takahiro, Moro-Martín, Amaya, Morrison, Debra L., Morrison, Jane, Morse, Ernie C., Moschos, Michael, Moseley, S. H., Mosier, Gary E., Mosner, Peter, Mountain, Matt, Muckenthaler, Jason S., Mueller, Donald G., Mueller, Migo, Muhiem, Daniella, Mühlmann, Prisca, Mullally, Susan Elizabeth, Mullen, Stephanie M., Munger, Alan J, Murphy, Jess, Murray, Katherine T., Muzerolle, James C., Mycroft, Matthew, Myers, Andrew, Myers, Carey R., Myers, Fred Richard R., Myers, Richard, Myrick, Kaila, Nagle IV, Adrian F., Nayak, Omnarayani, Naylor, Bret, Neff, Susan G., Nelan, Edmund P., Nella, John, Nguyen, Duy Tuong, Nguyen, Michael N., Nickson, Bryony, Nidhiry, John Joseph, Niedner, Malcolm B., Nieto-Santisteban, Maria, Nikolov, Nikolay K., Nishisaka, Mary Ann, Nota, Antonella, O'Mara, Robyn C., Oboryshko, Michael, O'Brien, Marcus B., Ochs, William R., Offenberg, Joel D., Ogle, Patrick Michael, Ohl, Raymond G., Olmsted, Joseph Hamden, Osborne, Shannon Barbara, O'Shaughnessy, Brian Patrick, Östlin, Göran, O'Sullivan, Brian, Otor, O. Justin, Ottens, Richard, Ouellette, Nathalie N. -Q., Outlaw, Daria J., Owens, Beverly A., Pacifici, Camilla, Page, James Christophe, Paranilam, James G., Park, Sang, Parrish, Keith A., Paschal, Laura, Patapis, Polychronis, Patel, Jignasha, Patrick, Keith, Pattishall Jr., Robert A., Paul, Douglas William, Paul, Shirley J., Pauly, Tyler Andrew, Pavlovsky, Cheryl M., Peña-Guerrero, Maria, Pedder, Andrew H., Peek, Matthew Weldon, Pelham, Patricia A., Penanen, Konstantin, Perriello, Beth A., Perrin, Marshall D., Perrine, Richard F., Perrygo, Chuck, Peslier, Muriel, Petach, Michael, Peterson, Karla A., Pfarr, Tom, Pierson, James M., Pietraszkiewicz, Martin, Pilchen, Guy, Pipher, Judy L., Pirzkal, Norbert, Pitman, Joseph T., Player, Danielle M., Plesha, Rachel, Plitzke, Anja, Pohner, John A., Poletis, Karyn Konstantin, Pollizzi, Joseph A., Polster, Ethan, Pontius, James T., Pontoppidan, Klaus, Porges, Susana C., Potter, Gregg D., Prescott, Stephen, Proffitt, Charles R., Pueyo, Laurent, Neira, Irma Aracely Quispe, Radich, Armando, Rager, Reiko T., Rameau, Julien, Ramey, Deborah D., Alarcon, Rafael Ramos, Rampini, Riccardo, Rapp, Robert, Rashford, Robert A., Rauscher, Bernard J., Ravindranath, Swara, Rawle, Timothy, Rawlings, Tynika N., Ray, Tom, Regan, Michael W., Rehm, Brian, Rehm, Kenneth D., Reid, Neill, Reis, Carl A., Renk, Florian, Reoch, Tom B., Ressler, Michael, Rest, Armin W., Reynolds, Paul J., Richon, Joel G., Richon, Karen V., Ridgaway, Michael, Riedel, Adric Richard, Rieke, George H., Rieke, Marcia, Rifelli, Richard E., Rigby, Jane R., Riggs, Catherine S., Ringel, Nancy J., Ritchie, Christine E., Rix, Hans-Walter, Robberto, Massimo, Robinson, Michael S., Robinson, Orion, Rock, Frank W., Rodriguez, David R., del Pino, Bruno Rodríguez, Roellig, Thomas, Rohrbach, Scott O., Roman, Anthony J., Romelfanger, Frederick J., Romo Jr., Felipe P., Rosales, Jose J., Rose, Perry, Roteliuk, Anthony F., Roth, Marc N., Rothwell, Braden Quinn, Rouzaud, Sylvain, Rowe, Jason, Rowlands, Neil, Roy, Arpita, Royer, Pierre, Rui, Chunlei, Rumler, Peter, Rumpl, William, Russ, Melissa L., Ryan, Michael B., Ryan, Richard M., Saad, Karl, Sabata, Modhumita, Sabatino, Rick, Sabbi, Elena, Sabelhaus, Phillip A., Sabia, Stephen, Sahu, Kailash C., Saif, Babak N., Salvignol, Jean-Christophe, Samara-Ratna, Piyal, Samuelson, Bridget S., Sanders, Felicia A., Sappington, Bradley, Sargent, B. A., Sauer, Arne, Savadkin, Bruce J., Sawicki, Marcin, Schappell, Tina M., Scheffer, Caroline, Scheithauer, Silvia, Scherer, Ron, Schiff, Conrad, Schlawin, Everett, Schmeitzky, Olivier, Schmitz, Tyler S., Schmude, Donald J., Schneider, Analyn, Schreiber, Jürgen, Schroeven-Deceuninck, Hilde, Schultz, John J., Schwab, Ryan, Schwartz, Curtis H., Scoccimarro, Dario, Scott, John F., Scott, Michelle B., Seaton, Bonita L., Seely, Bruce S., Seery, Bernard, Seidleck, Mark, Sembach, Kenneth, Shanahan, Clare Elizabeth, Shaughnessy, Bryan, Shaw, Richard A., Shay, Christopher Michael, Sheehan, Even, Sheth, Kartik, Shih, Hsin-Yi, Shivaei, Irene, Siegel, Noah, Sienkiewicz, Matthew G., Simmons, Debra D., Simon, Bernard P., Sirianni, Marco, Sivaramakrishnan, Anand, Slade, Jeffrey E., Sloan, G. C., Slocum, Christine E., Slowinski, Steven E., Smith, Corbett T., Smith, Eric P., Smith, Erin C., Smith, Koby, Smith, Robert, Smith, Stephanie J., Smolik, John L., Soderblom, David R., Sohn, Sangmo Tony, Sokol, Jeff, Sonneborn, George, Sontag, Christopher D., Sooy, Peter R., Soummer, Remi, Southwood, Dana M., Spain, Kay, Sparmo, Joseph, Speer, David T., Spencer, Richard, Sprofera, Joseph D., Stallcup, Scott S., Stanley, Marcia K., Stansberry, John A., Stark, Christopher C., Starr, Carl W., Stassi, Diane Y., Steck, Jane A., Steeley, Christine D., Stephens, Matthew A., Stephenson, Ralph J., Stewart, Alphonso C., Stiavelli, Massimo, Stockman Jr., Hervey, Strada, Paolo, Straughn, Amber N., Streetman, Scott, Strickland, David Kendal, Strobele, Jingping F., Stuhlinger, Martin, Stys, Jeffrey Edward, Such, Miguel, Sukhatme, Kalyani, Sullivan, Joseph F., Sullivan, Pamela C., Sumner, Sandra M., Sun, Fengwu, Sunnquist, Benjamin Dale, Swade, Daryl Allen, Swam, Michael S., Swenton, Diane F., Swoish, Robby A., Litten, Oi In Tam, Tamas, Laszlo, Tao, Andrew, Taylor, David K., Taylor, Joanna M., Plate, Maurice te, Van Tea, Mason, Teague, Kelly K., Telfer, Randal C., Temim, Tea, Texter, Scott C., Thatte, Deepashri G., Thompson, Christopher Lee, Thompson, Linda M., Thomson, Shaun R., Thronson, Harley, Tierney, C. M., Tikkanen, Tuomo, Tinnin, Lee, Tippet, William Thomas, Todd, Connor William, Tran, Hien D., Trauger, John, Trejo, Edwin Gregorio, Truong, Justin Hoang Vinh, Tsukamoto, Christine L., Tufail, Yasir, Tumlinson, Jason, Tustain, Samuel, Tyra, Harrison, Ubeda, Leonardo, Underwood, Kelli, Uzzo, Michael A., Vaclavik, Steven, Valenduc, Frida, Valenti, Jeff A., Van Campen, Julie, van de Wetering, Inge, Van Der Marel, Roeland P., van Haarlem, Remy, Vandenbussche, Bart, Vanterpool, Dona D., Vernoy, Michael R., Costas, Maria Begoña Vila, Volk, Kevin, Voorzaat, Piet, Voyton, Mark F., Vydra, Ekaterina, Waddy, Darryl J., Waelkens, Christoffel, Wahlgren, Glenn Michael, Walker Jr., Frederick E., Wander, Michel, Warfield, Christine K., Warner, Gerald, Wasiak, Francis C., Wasiak, Matthew F., Wehner, James, Weiler, Kevin R., Weilert, Mark, Weiss, Stanley B., Wells, Martyn, Welty, Alan D., Wheate, Lauren, Wheeler, Thomas P., White, Christy L., Whitehouse, Paul, Whiteleather, Jennifer Margaret, Whitman, William Russell, Williams, Christina C., Willmer, Christopher N. A., Willott, Chris J., Willoughby, Scott P., Wilson, Andrew, Wilson, Debra, Wilson, Donna V., Windhorst, Rogier, Wislowski, Emily Christine, Wolfe, David J., Wolfe, Michael A., Wolff, Schuyler, Wondel, Amancio, Woo, Cindy, Woods, Robert T., Worden, Elaine, Workman, William, Wright, Gillian S., Wu, Carl, Wu, Chi-Rai, Wun, Dakin D., Wymer, Kristen B., Yadetie, Thomas, Yan, Isabelle C., Yang, Keith C., Yates, Kayla L., Yeager, Christopher R., Yerger, Ethan John, Young, Erick T., Young, Gary, Yu, Gene, Yu, Susan, Zak, Dean S., Zeidler, Peter, Zepp, Robert, Zhou, Julia, Zincke, Christian A., Zonak, Stephanie, and Zondag, Elisabeth
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit., Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figures
Published: 2023
Full Text: View/download PDF

40. Clonal background and routes of plasmid transmission underlie antimicrobial resistance features of bloodstream Klebsiella pneumoniae

Author: Odion O. Ikhimiukor, Nicole I. Zac Soligno, Ifeoluwa J. Akintayo, Michael M. Marcovici, Stephanie S. R. Souza, Adrienne Workman, Isabella W. Martin, and Cheryl P. Andam
Subjects: Science
Abstract: Abstract Bloodstream infections caused by the opportunistic pathogen Klebsiella pneumoniae are associated with adverse health complications and high mortality rates. Antimicrobial resistance (AMR) limits available treatment options, thus exacerbating its public health and clinical burden. Here, we aim to elucidate the population structure of K. pneumoniae in bloodstream infections from a single medical center and the drivers that facilitate the dissemination of AMR. Analysis of 136 short-read genome sequences complemented with 12 long-read sequences shows the population consisting of 94 sequence types (STs) and 99 clonal groups, including globally distributed multidrug resistant and hypervirulent clones. In vitro antimicrobial susceptibility testing and in silico identification of AMR determinants reveal high concordance (90.44–100%) for aminoglycosides, beta-lactams, carbapenems, cephalosporins, quinolones, and sulfonamides. IncF plasmids mediate the clonal (within the same lineage) and horizontal (between lineages) transmission of the extended-spectrum beta-lactamase gene bla CTX-M-15. Nearly identical plasmids are recovered from isolates over a span of two years indicating long-term persistence. The genetic determinants for hypervirulence are carried on plasmids exhibiting genomic rearrangement, loss, and/or truncation. Our findings highlight the importance of considering both the genetic background of host strains and the routes of plasmid transmission in understanding the spread of AMR in bloodstream infections.
Published: 2024
Full Text: View/download PDF

41. The Impact of COVID-19: Faculty Perspectives on Community-Based Learning

Author: Andrade, Maureen Snow, Workman, Letty, and Westover, Jonathan H.
Abstract: Community-based learning (CBL) is a mutually beneficial partnership involving higher education institutions (HEIs), students, faculty, and the community. It provides students with the opportunity to apply academic concepts to real-life situations and community organizations with the opportunity to gain insights from evidence-based theories and current research. Significant changes for HEIs and businesses resulting from the COVID-19 pandemic, such as online course delivery, business lockdowns, telecommuting, and physical distancing, suggest a large potential impact on CBL practice and increased challenges for faculty members who manage CBL processes. This study explores the faculty perspective on CBL practices with a specific focus on the impact of COVID-19. Findings indicate that both institutions and faculty within them found innovative solutions for overcoming disruptions caused by the pandemic. The findings also indicate a range of practices related to support and training for CBL and overwhelming indicate strong faculty commitment to pedagogical approaches that deepen student learning while also benefiting local communities.
Published: 2022

42. Making Connections to Address Mathematics Anxiety: A Case Study of the Instructional Triangle and Remedial College Instructors

Author: Pringle, Njeri M., Workman, Jamie L., and Arrastia-Chisholm, Meagan C.
Abstract: Mathematics anxiety is a reality for many students as a number of community college and four-year university students feel disconnected from math and struggle to pass mathematics courses. Using a case study and grounded theory approach, six remedial mathematics instructors were interviewed and observed to examine their instructional strategies and practices. During the interviews, participants expounded upon the changes in strategies and practices implemented when aiding students struggling with anxiety. "The Instructional Triangle" was applied across participants to compare and contrast their experiences. The analysis focused on environmental factors that could increase or exacerbate mathematics anxiety. In particular, a theme of creating connections emerged from how teachers assess for and adjust their strategies and practices to support remedial mathematics students struggling with anxiety. Based on the findings, interventions for assisting educators and students in mediating anxiety promoting perspective-taking and empathy are recommended. Such intervention could inform future strategy and practice development, implementation, and evaluation.
Published: 2022

43. In Search of Safety: A Case Study of LGBT+ College Students' Perception of Safe Spaces at a Rural University

Author: Ryan Campen, Jamie L. Workman, and James G. Archibald
Abstract: The purpose of this study was to better understand how LGBT+ college students find a safe space on college and university campuses when there is not one already provided for them. Strange and Banning's (2015) four environments served as the theoretical framework. Data were collected through individual interviews with six college students who identify within the LGBT+ community and attend a mid-sized institution in South Georgia which does not have an established safe space. Students indicated locations like the library, front lawn, and individuals such as faculty, staff, and student organizations offered safe spaces. The results can better inform student affairs educators or any professional who works with LGBT+ populations on how to better support these students while they are under their guise. It also supports the trend of colleges and universities establishing safe spaces for their LGBT+ students.
Published: 2022

44. GPT-4 Technical Report

Author: OpenAI, Achiam, Josh, Adler, Steven, Agarwal, Sandhini, Ahmad, Lama, Akkaya, Ilge, Aleman, Florencia Leoni, Almeida, Diogo, Altenschmidt, Janko, Altman, Sam, Anadkat, Shyamal, Avila, Red, Babuschkin, Igor, Balaji, Suchir, Balcom, Valerie, Baltescu, Paul, Bao, Haiming, Bavarian, Mohammad, Belgum, Jeff, Bello, Irwan, Berdine, Jake, Bernadett-Shapiro, Gabriel, Berner, Christopher, Bogdonoff, Lenny, Boiko, Oleg, Boyd, Madelaine, Brakman, Anna-Luisa, Brockman, Greg, Brooks, Tim, Brundage, Miles, Button, Kevin, Cai, Trevor, Campbell, Rosie, Cann, Andrew, Carey, Brittany, Carlson, Chelsea, Carmichael, Rory, Chan, Brooke, Chang, Che, Chantzis, Fotis, Chen, Derek, Chen, Sully, Chen, Ruby, Chen, Jason, Chen, Mark, Chess, Ben, Cho, Chester, Chu, Casey, Chung, Hyung Won, Cummings, Dave, Currier, Jeremiah, Dai, Yunxing, Decareaux, Cory, Degry, Thomas, Deutsch, Noah, Deville, Damien, Dhar, Arka, Dohan, David, Dowling, Steve, Dunning, Sheila, Ecoffet, Adrien, Eleti, Atty, Eloundou, Tyna, Farhi, David, Fedus, Liam, Felix, Niko, Fishman, Simón Posada, Forte, Juston, Fulford, Isabella, Gao, Leo, Georges, Elie, Gibson, Christian, Goel, Vik, Gogineni, Tarun, Goh, Gabriel, Gontijo-Lopes, Rapha, Gordon, Jonathan, Grafstein, Morgan, Gray, Scott, Greene, Ryan, Gross, Joshua, Gu, Shixiang Shane, Guo, Yufei, Hallacy, Chris, Han, Jesse, Harris, Jeff, He, Yuchen, Heaton, Mike, Heidecke, Johannes, Hesse, Chris, Hickey, Alan, Hickey, Wade, Hoeschele, Peter, Houghton, Brandon, Hsu, Kenny, Hu, Shengli, Hu, Xin, Huizinga, Joost, Jain, Shantanu, Jain, Shawn, Jang, Joanne, Jiang, Angela, Jiang, Roger, Jin, Haozhun, Jin, Denny, Jomoto, Shino, Jonn, Billie, Jun, Heewoo, Kaftan, Tomer, Kaiser, Łukasz, Kamali, Ali, Kanitscheider, Ingmar, Keskar, Nitish Shirish, Khan, Tabarak, Kilpatrick, Logan, Kim, Jong Wook, Kim, Christina, Kim, Yongjik, Kirchner, Jan Hendrik, Kiros, Jamie, Knight, Matt, Kokotajlo, Daniel, Kondraciuk, Łukasz, Kondrich, Andrew, Konstantinidis, Aris, Kosic, Kyle, Krueger, Gretchen, Kuo, Vishal, Lampe, Michael, Lan, Ikai, Lee, Teddy, Leike, Jan, Leung, Jade, Levy, Daniel, Li, Chak Ming, Lim, Rachel, Lin, Molly, Lin, Stephanie, Litwin, Mateusz, Lopez, Theresa, Lowe, Ryan, Lue, Patricia, Makanju, Anna, Malfacini, Kim, Manning, Sam, Markov, Todor, Markovski, Yaniv, Martin, Bianca, Mayer, Katie, Mayne, Andrew, McGrew, Bob, McKinney, Scott Mayer, McLeavey, Christine, McMillan, Paul, McNeil, Jake, Medina, David, Mehta, Aalok, Menick, Jacob, Metz, Luke, Mishchenko, Andrey, Mishkin, Pamela, Monaco, Vinnie, Morikawa, Evan, Mossing, Daniel, Mu, Tong, Murati, Mira, Murk, Oleg, Mély, David, Nair, Ashvin, Nakano, Reiichiro, Nayak, Rajeev, Neelakantan, Arvind, Ngo, Richard, Noh, Hyeonwoo, Ouyang, Long, O'Keefe, Cullen, Pachocki, Jakub, Paino, Alex, Palermo, Joe, Pantuliano, Ashley, Parascandolo, Giambattista, Parish, Joel, Parparita, Emy, Passos, Alex, Pavlov, Mikhail, Peng, Andrew, Perelman, Adam, Peres, Filipe de Avila Belbute, Petrov, Michael, Pinto, Henrique Ponde de Oliveira, Michael, Pokorny, Pokrass, Michelle, Pong, Vitchyr H., Powell, Tolly, Power, Alethea, Power, Boris, Proehl, Elizabeth, Puri, Raul, Radford, Alec, Rae, Jack, Ramesh, Aditya, Raymond, Cameron, Real, Francis, Rimbach, Kendra, Ross, Carl, Rotsted, Bob, Roussez, Henri, Ryder, Nick, Saltarelli, Mario, Sanders, Ted, Santurkar, Shibani, Sastry, Girish, Schmidt, Heather, Schnurr, David, Schulman, John, Selsam, Daniel, Sheppard, Kyla, Sherbakov, Toki, Shieh, Jessica, Shoker, Sarah, Shyam, Pranav, Sidor, Szymon, Sigler, Eric, Simens, Maddie, Sitkin, Jordan, Slama, Katarina, Sohl, Ian, Sokolowsky, Benjamin, Song, Yang, Staudacher, Natalie, Such, Felipe Petroski, Summers, Natalie, Sutskever, Ilya, Tang, Jie, Tezak, Nikolas, Thompson, Madeleine B., Tillet, Phil, Tootoonchian, Amin, Tseng, Elizabeth, Tuggle, Preston, Turley, Nick, Tworek, Jerry, Uribe, Juan Felipe Cerón, Vallone, Andrea, Vijayvergiya, Arun, Voss, Chelsea, Wainwright, Carroll, Wang, Justin Jay, Wang, Alvin, Wang, Ben, Ward, Jonathan, Wei, Jason, Weinmann, CJ, Welihinda, Akila, Welinder, Peter, Weng, Jiayi, Weng, Lilian, Wiethoff, Matt, Willner, Dave, Winter, Clemens, Wolrich, Samuel, Wong, Hannah, Workman, Lauren, Wu, Sherwin, Wu, Jeff, Wu, Michael, Xiao, Kai, Xu, Tao, Yoo, Sarah, Yu, Kevin, Yuan, Qiming, Zaremba, Wojciech, Zellers, Rowan, Zhang, Chong, Zhang, Marvin, Zhao, Shengjia, Zheng, Tianhao, Zhuang, Juntang, Zhuk, William, and Zoph, Barret
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-world scenarios, GPT-4 exhibits human-level performance on various professional and academic benchmarks, including passing a simulated bar exam with a score around the top 10% of test takers. GPT-4 is a Transformer-based model pre-trained to predict the next token in a document. The post-training alignment process results in improved performance on measures of factuality and adherence to desired behavior. A core component of this project was developing infrastructure and optimization methods that behave predictably across a wide range of scales. This allowed us to accurately predict some aspects of GPT-4's performance based on models trained with no more than 1/1,000th the compute of GPT-4., Comment: 100 pages; updated authors list; fixed author names and added citation
Published: 2023

45. Leveraging Contextual Relatedness to Identify Suicide Documentation in Clinical Notes through Zero Shot Learning

Author: Workman, Terri Elizabeth, Goulet, Joseph L., Brandt, Cynthia A., Warren, Allison R., Eleazer, Jacob, Skanderson, Melissa, Lindemann, Luke, Blosnich, John R., Leary, John O, and Treitler, Qing Zeng
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computation and Language, I.2.7, J.3
Abstract: Identifying suicidality including suicidal ideation, attempts, and risk factors in electronic health record data in clinical notes is difficult. A major difficulty is the lack of training samples given the small number of true positive instances among the increasingly large number of patients being screened. This paper describes a novel methodology that identifies suicidality in clinical notes by addressing this data sparsity issue through zero-shot learning. U.S. Veterans Affairs clinical notes served as data. The training dataset label was determined using diagnostic codes of suicide attempt and self-harm. A base string associated with the target label of suicidality was used to provide auxiliary information by narrowing the positive training cases to those containing the base string. A deep neural network was trained by mapping the training documents contents to a semantic space. For comparison, we trained another deep neural network using the identical training dataset labels and bag-of-words features. The zero shot learning model outperformed the baseline model in terms of AUC, sensitivity, specificity, and positive predictive value at multiple probability thresholds. In applying a 0.90 probability threshold, the methodology identified notes not associated with a relevant ICD 10 CM code that documented suicidality, with 94 percent accuracy. This new method can effectively identify suicidality without requiring manual annotation., Comment: 8 pages, 4 figures, 5 tables
Published: 2023

46. Risk Factors for Adults with Chronic Obstructive Pulmonary Disease in the United States, Utilizing State-Based Surveillance

Author: Brandon Workman and Laura Nabors
Subjects: Chronic Obstructive Pulmonary Disease, comorbidities, population-based study, patient-reported outcomes, racial and ethnic differences, tobacco use, Diseases of the respiratory system, RC705-779
Abstract: Chronic Obstructive Pulmonary Disease (COPD) is a complex and heterogeneous condition. Exposure to tobacco smoke and air pollutants are key risk factors for COPD development; however, other risk factors include race/ethnicity, sex of adults, a history of asthma, occupational exposures, and chronic respiratory infections. Data for the current study were from the 2022 Behavioral Risk Factor Surveillance Survey. Chi-squares and multinomial logistic regression analyses, adjusted with the survey’s sampling weight, were used to examine how critical health indicators impacted a COPD diagnosis. Participants (N = 311,175) were adults aged 45 years and older. Adjusted multinomial regression analyses showed adults who reported asthma, current and former smoking, poor physical health, depression, less physical activity, and fatigue were more likely to report COPD. Those with COPD were more likely to be male than female. Moreover, those with COPD reported higher rates of health insurance coverage, and yet had lower income and more financial difficulty affording a doctor for health services. In a follow up regression analysis, examining racial differences in COPD for participants, American Indian adults had a higher odds of reporting COPD than the “other” race groups. Because COPD remains a leading cause of death and disability in the U.S., and racial disparities persist in respiratory outcomes, continuing to identify risk factors for vulnerable groups could assist health program planners with development of successful health messaging.
Published: 2024
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47. Prevalent Atherosclerotic Cardiovascular Disease Among Veterans by Sexual Orientation

Author: Carl G. Streed, Meredith S. Duncan, Kory R. Heier, T. Elizabeth Workman, Lauren B. Beach, Billy A. Caceres, John R. O'Leary, Melissa Skanderson, and Joseph L. Goulet
Subjects: bisexual, cardiovascular, gay, heart attack, lesbian, sexual minority, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background Seven million lesbian, gay, and bisexual (LGB) adults will be aged >50 years by 2030; assessing and addressing their risk for cardiovascular disease is critical. Methods and Results We analyzed a nationwide cohort using the Veterans Health Administration data. Sexual orientation (SO) was classified via a validated natural language processing algorithm. Prevalent atherosclerotic cardiovascular disease (ASCVD) (history of acute myocardial infarction, ischemic stroke, or revascularization) was identified via International Classification of Diseases, Ninth and Tenth Revision (ICD‐9 and ICD‐10) codes. The index date was the date of the first primary care appointment on or after October 1, 2009. We ascertained covariates and prevalent ASCVD in the year following the index date; the baseline date was 1 year after the index date. We calculated sample statistics by sex and SO and used logistic regression analyses to assess associations between SO and prevalent ASCVD. Of 1 102 193 veterans with natural language processing‐defined SO data, 170 861 were classified as LGB. Prevalent ASCVD was present among 25 031 (4105 LGB). Adjusting for age, sex, race, and Hispanic ethnicity, LGB veterans had 1.24 [1.19–1.28] greater odds of prevalent ASCVD versus non‐LGB identified veterans. This association remained significant upon additional adjustment for the ASCVD risk factors substance use, anxiety, and depression (odds ratio [OR],1.17 [95% CI, 1.13–1.21]). Among a subset with self‐reported SO, findings were consistent (OR, 1.53 [95% CI, 1.20–1.95]). Conclusions This is one of the first studies to examine cardiovascular risk factors and disease of the veteran population stratified by natural language processing‐defined SO. Future research must explore psychological, behavioral, and physiological mechanisms that result in poorer cardiovascular health among LGB veterans.
Published: 2024
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48. Rural service coordination programming for women using substances and their families

Author: Lesley Cottrell, Charlotte Workman, Melina Danko, Ellis Walker, Anthony Dmytrijuk, Susan Harrison, Mikisha Lee, Ashleigh McKinsey, and Mark C Smith
Subjects: 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
Published: 2024
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49. Author Correction: Aplp1 interacts with Lag3 to facilitate transmission of pathologic α-synuclein

Author: Xiaobo Mao, Hao Gu, Donghoon Kim, Yasuyoshi Kimura, Ning Wang, Enquan Xu, Ramhari Kumbhar, Xiaotian Ming, Haibo Wang, Chan Chen, Shengnan Zhang, Chunyu Jia, Yuqing Liu, Hetao Bian, Senthilkumar S. Karuppagounder, Fatih Akkentli, Qi Chen, Longgang Jia, Heehong Hwang, Su Hyun Lee, Xiyu Ke, Michael Chang, Amanda Li, Jun Yang, Cyrus Rastegar, Manjari Sriparna, Preston Ge, Saurav Brahmachari, Sangjune Kim, Shu Zhang, Yasushi Shimoda, Martina Saar, Haiqing Liu, Sin Ho Kweon, Mingyao Ying, Creg J. Workman, Dario A. A. Vignali, Ulrike C. Muller, Cong Liu, Han Seok Ko, Valina L. Dawson, and Ted M. Dawson
Subjects: Science
Published: 2024
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50. Large-scale differentiation of iPSC-derived motor neurons from ALS and control subjects

Author: Workman, Michael J, Lim, Ryan G, Wu, Jie, Frank, Aaron, Ornelas, Loren, Panther, Lindsay, Galvez, Erick, Perez, Daniel, Meepe, Imara, Lei, Susan, Valencia, Viviana, Gomez, Emilda, Liu, Chunyan, Moran, Ruby, Pinedo, Louis, Tsitkov, Stanislav, Ho, Ritchie, Kaye, Julia A, Consortium, the Answer ALS, Thompson, Terri, Rothstein, Jeffrey D, Finkbeiner, Steven, Fraenkel, Ernest, Sareen, Dhruv, Thompson, Leslie M, and Svendsen, Clive N
Subjects: Biomedical and Clinical Sciences, Neurosciences, Brain Disorders, Clinical Research, Stem Cell Research - Induced Pluripotent Stem Cell - Human, Rare Diseases, Stem Cell Research - Induced Pluripotent Stem Cell, Regenerative Medicine, Genetics, Neurodegenerative, Stem Cell Research, ALS, Orphan Drug, Neurological, Humans, Amyotrophic Lateral Sclerosis, Induced Pluripotent Stem Cells, Motor Neurons, Cell Differentiation, Answer ALS Consortium, iPSC, motor neurons, sex differences, Psychology, Cognitive Sciences, Neurology & Neurosurgery, Biological psychology
Abstract: Using induced pluripotent stem cells (iPSCs) to understand the mechanisms of neurological disease holds great promise; however, there is a lack of well-curated lines from a large array of participants. Answer ALS has generated over 1,000 iPSC lines from control and amyotrophic lateral sclerosis (ALS) patients along with clinical and whole-genome sequencing data. The current report summarizes cell marker and gene expression in motor neuron cultures derived from 92 healthy control and 341 ALS participants using a 32-day differentiation protocol. This is the largest set of iPSCs to be differentiated into motor neurons, and characterization suggests that cell composition and sex are significant sources of variability that need to be carefully controlled for in future studies. These data are reported as a resource for the scientific community that will utilize Answer ALS data for disease modeling using a wider array of omics being made available for these samples.
Published: 2023

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