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14,218 results on '"Ross, S."'

7. Phase I Trial of MCARH109, a G Protein–Coupled Receptor Class C Group 5 Member D (GPRC5D)-Targeted Chimeric Antigen Receptor T-Cell Therapy for Multiple Myeloma: An Updated Analysis

Author

Jurgens, Eric M., Firestone, Ross S., Chaudhari, Jagrutiben, Hosszu, Kinga, Devlin, Sean M., Shah, Urvi A., Landa, Jonathan, McAvoy, Devin P., Lesokhin, Alexander M., Korde, Neha, Hassoun, Hani, Tan, Carlyn R., Hultcrantz, Malin, Shah, Gunjan L., Landau, Heather J., Chung, David J., Scordo, Michael, Eren, Ozgur Can, Dogan, Ahmet, Giralt, Sergio A., Park, Jae H., Rivière, Isabelle, Brentjens, Renier J., Smith, Eric L., Wang, Xiuyan, Usmani, Saad Z., and Mailankody, Sham

Published
2024
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8. Extracting sensory experiences and cultural ecosystem services from actively crowdsourced descriptions of everyday lived landscapes

Author

Manuel F. Baer, Flurina Wartmann, Nora Fagerholm, and Ross S. Purves

Subjects
Christian Albert, Active crowdsourcing, cultural ecosystem services, everyday lived landscapes, multi-sensory landscape perception, natural language processing, Human ecology. Anthropogeography, GF1-900, Environmental sciences, GE1-350
Abstract

What cultural ecosystem services (CES) do people perceive in their immediate surroundings, and what sensory experiences are linked to these ecosystem services? And how are these CES and experiences expressed in natural language? In this study, we used data generated through a gamified application called Window Expeditions, where people uploaded short descriptions of landscapes they were able to experience through their windows during the COVID-19 pandemic. We used a combination of annotation, close reading and distant reading using natural language processing and graph analysis to extract CES and sensory experiences and link these to biophysical landscape elements. In total, 272 users contributed 373 descriptions in English across more than 40 countries. Of the cultural ecosystem services, recreation was the most prominently described, followed by heritage, identity and tranquility. Descriptions of sensory experiences focused on the visual but also included auditory experiences and touch and feel. Sensory experiences and cultural ecosystem services varied according to biophysical landscape elements, with, for example, animals being more associated with sound and touch/feel and heritage being more associated with moving objects and the built environment. Sentiments also varied across the senses, with the visual being more strongly associated with positive experiences than other senses. This study showed how a hybrid approach combining manual analysis and natural language processing can be productively applied to landscape descriptions generated by members of the public, and how CES on everyday lived landscapes can be extracted from such data sources.

Published
2024
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10. Landschaft und Freizeit

Author

Backhaus, Norman, Hunziker, Marcel, Purves, Ross S., Siegrist, Dominik, Kühne, Olaf, Series Editor, Kinder, Sebastian, Series Editor, Schnur, Olaf, Series Editor, Weber, Florian, editor, Berr, Karsten, editor, and Jenal, Corinna, editor

Published
2024
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19. Kepler K2 Campaign 9: II. First space-based discovery of an exoplanet using microlensing

Author

Specht, D., Poleski, R., Penny, M. T., Kerins, E., McDonald, I., Lee, Chung-Uk, Udalski, A., Bond, I. A., Shvartzvald, Y., Zang, Weicheng, Street, R. A., Hogg, D. W., Gaudi, B. S., Barclay, T., Barentsen, G., Howell, S. B., Mullally, F., Henderson, C. B., Bryson, S. T., Caldwell, D. A., Haas, M. R., Van Cleve, J. E., Larson, K., McCalmont, K., Peterson, C., Putnam, D., Ross, S., Packard, M., Reedy, L., Albrow, Michael D., Chung, Sun-Ju, Jung, Youn Kil, Gould, Andrew, Han, Cheongho, Hwang, Kyu-Ha, Ryu, Yoon-Hyun, Shin, In-Gu, Yang, Hongjing, Yee, Jennifer C., Cha, Sang-Mok, Kim, Dong-Jin, Kim, Seung-Lee, Lee, Dong-Joo, Lee, Yongseok, Park, Byeong-Gon, Pogge, Richard W., Szymański, M. K., Soszyński, I., Ulaczyk, K., Pietrukowicz, P., Kozlowski, Sz., Skowron, J., Mróz, P., Mao, Shude, Fouqué, Pascal, Zhu, Wei, Abe, F., Barry, R., Bennett, D. P., Bhattacharya, A., Fukui, A., Fujii, H., Hirao, Y., Itow, Y., Kirikawa, R., Kondo, I., Koshimoto, N., Matsubara, Y., Matsumoto, S., Miyazaki, S., Muraki, Y., Olmschenk, G., Ranc, C., Okamura, A., Rattenbury, N. J., Satoh, Y., Sumi, T., Suzuki, D., Silva, S. I., Toda, T., Tristram, P. J., Vandorou, A., Yama, H., Beichman, C., Bryden, G., and Novati, S. Calchi

Subjects
Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract

We present K2-2016-BLG-0005Lb, a densely sampled, planetary binary caustic-crossing microlensing event found from a blind search of data gathered from Campaign 9 of the Kepler K2 mission (K2C9). K2-2016-BLG-0005Lb is the first bound microlensing exoplanet discovered from space-based data. The event has caustic entry and exit points that are resolved in the K2C9 data, enabling the lens--source relative proper motion to be measured. We have fitted a binary microlens model to the Kepler data, and to simultaneous observations from multiple ground-based surveys. Whilst the ground-based data only sparsely sample the binary caustic, they provide a clear detection of parallax that allows us to break completely the microlensing mass--position--velocity degeneracy and measure the planet's mass directly. We find a host mass of $0.58\pm0.04 ~{\rm M}_\odot$ and a planetary mass of $1.1\pm0.1 ~{\rm M_J}$. The system lies at a distance of $5.2\pm0.2~$kpc from Earth towards the Galactic bulge, more than twice the distance of the previous most distant planet found by Kepler. The sky-projected separation of the planet from its host is found to be $4.2\pm0.3~$au which, for circular orbits, deprojects to a host separation $a = 4.4^{+1.9}_{-0.4}~$au and orbital period $P = 13^{+9}_{-2}~$yr. This makes K2-2016-BLG-0005Lb a close Jupiter analogue orbiting a low-mass host star. According to current planet formation models, this system is very close to the host mass threshold below which Jupiters are not expected to form. Upcoming space-based exoplanet microlensing surveys by NASA's Nancy Grace Roman Space Telescope and, possibly, ESA's Euclid mission, will provide demanding tests of current planet formation models., Comment: 18 pages. Accepted for publication in MNRAS Published by Oxford University Press on behalf of the Royal Astronomical Society

Published
2022
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20. The Shriners Children's Standard Gait Model (SCGM)

Author

Kruger, Karen M., Fischer, Patrick, Augsburger, Sam, Feng, Jing, Girouard, Jean-Francois, Gregory, Daniel L., Johnson, Logan, MacWilliams, Bruce A., McMulkin, Mark L., Nelson, Bradley, Warshauer, Spencer, Saraswat, Prabhav, and Chafetz, Ross S.

Published
2024
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22. Seeing through a new lens: exploring the potential of city walking tour videos for urban analytics

Author

Maximilian C. Hartmann and Ross S. Purves

Subjects
street-level imagery, city walking tour videos, transport modes, mobility, object detection, geolocation, Mathematical geography. Cartography, GA1-1776
Abstract

City Walking Tour Videos (CWTVs) are a novel source of Volunteered Geographic Information providing street-level imagery through video sharing platforms such as YouTube. We demonstrate that these videos contain rich information for urban analytical applications, by conducting a mobility study. We detect transport modes with a focus on active (pedestrians and cyclists) and motorised mobility (cars, motorcyclists and trucks). We chose the City of Paris as our area of interest given the rapid expansion of the bicycle network as a response to the Covid-19 pandemic and compiled a video corpus encompassing more than 66 hours of video footage. Through the detection of street names in the video and placename containing timestamps we extracted and georeferenced 1169 locations at which we summarise the detected transport modes. Our results show high potential of CWTVs for studying urban mobility applications. We detected significant shifts in the mobility mix before and during the pandemic as well as weather effects on the volumes of pedestrians and cyclists. Combined with the observed increase in data availability over the years we suggest that CWTVs have considerable potential for other applications in the field of urban analytics.

Published
2023
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23. Patterns of CRS with teclistamab in relapsed/refractory multiple myeloma with or without prior T-cell redirection therapy

Author

Hamadeh, Issam S., Shekarkhand, Tala, Rueda, Colin, Firestone, Ross S., Wang, Alice X., Korde, Neha, Hultcrantz, Malin L., Lesokhin, Alexander M., Mailankody, Sham, Hassoun, Hani, Shah, Urvi A., Maclachlan, Kylee, Rajeeve, Sridevi, Patel, Dhwani, Shah, Gunjan L., Scordo, Michael, Lahoud, Oscar B., Chung, David J., Landau, Heather J., Giralt, Sergio, Usmani, Saad Z., and Tan, Carlyn R.

Published
2024
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24. Unscheduled health care interactions in patients with multiple myeloma receiving T-cell redirection therapies

Author

Howard, Anna J., Concepcion, Isabel, Wang, Alice X., Hamadeh, Issam S., Hultcrantz, Malin, Mailankody, Sham, Tan, Carlyn, Korde, Neha, Lesokhin, Alexander M., Hassoun, Hani, Shah, Urvi A., Maclachlan, Kylee H., Rajeeve, Sridevi, Landau, Heather J., Scordo, Michael, Shah, Gunjan L., Lahoud, Oscar B., Chung, David J., Giralt, Sergio, Usmani, Saad Z., and Firestone, Ross S.

Published
2024
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27. The Shriners Children’s Gait Model (SCGM)

Author

Kruger, Karen M., Fischer, Patrick, Augsburger, Sam, Feng, Jing, Girouard, Jean-Francois, Gregory, Daniel L., Johnson, Logan, MacWilliams, Bruce A., McMulkin, Mark L., Nelson, Bradley, Warshauer, Spencer, Saraswat, Prabhav, and Chafetz, Ross S.

Published
2024
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30. CD8 effector T cells enhance teclistamab response in BCMA-exposed and -naïve multiple myeloma

Author

Firestone, Ross S., McAvoy, Devin, Shekarkhand, Tala, Serrano, Edith, Hamadeh, Issam, Wang, Alice, Zhu, Menglei, Qin, Wei Ge, Patel, Dhwani, Tan, Carlyn R., Hultcrantz, Malin, Mailankody, Sham, Hassoun, Hani, Shah, Urvi S., Korde, Neha, Maclachlan, Kylee H., Landau, Heather J., Scordo, Michael, Shah, Gunjan L., Lahoud, Oscar B., Giralt, Sergio, Murata, Kazunori, Hosszu, Kinga K., Chung, David J., Lesokhin, Alexander M., and Usmani, Saad Z.

Published
2024
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33. The energy of muscle contraction. II. Transverse compression and work

Author

Ryan, D. S., Domínguez, S., Ross, S. A., Nigam, N., and Wakeling, J. M.

Subjects
Quantitative Biology - Tissues and Organs, Quantitative Biology - Quantitative Methods
Abstract

In this study we reproduced this compression-induced reduction in muscle force through the use of a three-dimensional finite element model of contracting muscle. The model used the principle of minimum total energy and allowed for the redistribution of energy through different strain energy-densities; this allowed us to determine the importance of the strain energy-densities to the transverse forces developed by the muscle. Furthermore, we were able to study how external work done on the muscle by transverse compression affects the internal work and strain-energy distribution of the muscle., Comment: 20 pages, 7 figures. Manuscript submitted to Frontiers in Physiology

Published
2020
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40. PERSUADE Survey—PERioperative AnestheSia and Intensive Care Management of Left VentricUlar Assist DevicE Implantation in Europe and the United States

Author

Alfirevic, Andrej, Anton, James M., Antoniou, Theofani, Auci, Elisabetta, Badakhsh, Orode, Banks, Dalia A., Barrio, Jose M., Bartels, Karsten, Belli, Erol V., Bermede, Onat, Bettex, Dominique, Biedermann, Sébastien, Boelsen, Jonas, Boisen, Michael L., Book, Malte, Bottiger, Brandi A., Bouchez, Stefaan, Bräuer, Anselm, Brodt, Jessica L, Chaudhry, Sunit-Preet, Conlin, Frederick T., Cormican, Daniel S., Cristinar, Mircea, Curtis, Michael S., Dalia, Adam A., D'Avino, Emilio, Durand, Michel, Eberle, Balthasar, Emmert, Daniel A., Erb, Joachim M., Falterman, Jason, Forner, Anna Flo, Gatha, Nehal M., Gaudard, Philippe, Giebler, Antasia, Gliga, Louise A., Guarracino, Fabio, Gürcü, Mustafa E., Hans, Gregory A., Hanson, Ross S., Heringlake, Matthias, Hilberath, Jan N., Hommel, Matthias, Huhn, Ragnar, Iyer, Manoj H., Jacquet, Luc M., Karadeniz, Ümit, Kertai, Miklos D., Martin, Archer Kilbourne, Kolarczyk, Lavinia M., Koller, Tobias, Kurian, Dinesh J., Kornfield, Zev N., Koster, Andreas, Kranke, Peter, Krauss, Bernadette, Kudsioglu, Turkan, Kwak, Jenny, Lachauer, Steffen, Lagier, David, Lango, Romuald, Liang, Hong, Lilie, Craig J., Logeman, Elisabeth Angelique, Magunia, Harry, Mahmoud, Saifeldin, Makar, Moody, Markovic, Dejan, Mathis, Michael R., Mattei, Mathieu, Mazzeffi, Michael A., McCabe, Melissa D., Meers, J. Brad, Moitra, Vivek K., Møller-Sørensen, Hasse, Moravcova, Sarka, Muellejans, Bernd, Münch, Christopher M., Murray, Andrew W., Moncho, Azucena Pajares, Ngai, Jennie, Nielsen, Dorthe V., Ortoleva, Jamel P., Ouattara, Alexandre, Patel, Bhoumesh, Paul, Frank, Peng, Yong G., Pittarello, Demetrio, Prabhu, Mahesh, Rancati, Valentina, Rex, Steffen, Riha, Hynek, Robitaille, Mark J., Blanco, Yiliam Rodriguez, Rovira, Irene, Ruusalepp, Arno, Samalavicius, Robertas, Saatee, Siavosh, Sauer, William J., Scheiermann, Patrick, Schlesinger, Rachel E., Schroeder, Andrew M., Schroeder, Sarah E., Shih, Henry, Slaughter, Mark S., Sostaric, Maja, Šribar, Andrej, Svalebjørg, Morten, Székely, Andrea, Szentgyorgyi, Lajos, ter Horst, Maarten, Tschernko, Edda M., Twite, Mark, Ulrichs, Christoph, van der Maaten, Joost M.A.A., van der Ploeg, Nathalie, Vilela, Hugo P., von Homeyer, Peter, Wagner, Nana-Maria, Weiner, Menachem M., Wunder, Christian, Zink, Wolfgang, Kummerow, Maren, von Dossow, Vera, Pasero, Daniela, Martinez Lopez de Arroyabe, Blanca, Abrams, Benjamin, Kowalsky, Markus, Wilkey, Barbara J., Subramanian, Kathirvel, Martin, Archer K., Marczin, Nandor, and de Waal, Eric E.C.

Published
2024
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45. The energy of muscle contraction. I. Tissue force and deformation during isometric contractions

Author

Wakeling, J. M., Ross, S. A., Ryan, D. S., Bolsterlee, B., Konno, R., Domínguez, S., and Nigam, N.

Subjects
Physics - Biological Physics, Mathematics - Numerical Analysis
Abstract

During contraction the energy of muscle tissue increases due to energy from the hydrolysis of ATP. This energy is distributed across the tissue as strain-energy potentials in the contractile elements, strain-energy potential from the 3D deformation of the base-material tissue (containing cellular and ECM effects), energy related to changes in the muscle's nearly incompressible volume and external work done at the muscle surface. Thus, energy is redistributed through the muscle's tissue as it contracts, with only a component of this energy being used to do mechanical work and develop forces in the muscle's line-of-action. Understanding how the strain-energy potentials are redistributed through the muscle tissue will help enlighten why the mechanical performance of whole muscle in its line-of-action does not match the performance that would be expected from the contractile elements alone. Here we demonstrate these physical effects using a 3D muscle model based on the finite element method. The tissue deformations within contracting muscle are large, and so the mechanics of contraction were explained using the principles of continuum mechanics for large deformations. We present simulations of a contracting medial gastrocnemius muscle, showing tissue deformations that mirror observations from MRI-based images. This paper tracks the redistribution of strain-energy potentials through the muscle tissue during isometric contractions, and shows how fibre shortening, pennation angle, transverse bulging and anisotropy in the stress and strain of the muscle tissue are all related to the interaction between the material properties of the muscle and the action of the contractile elements., Comment: 42 pages, 12 figures. Manuscripts submitted to Frontiers in Physiology

Published
2020
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46. The impact of the distance traveled between residence and gestational trophoblastic neoplasia reference center and clinical outcomes in Brazilian women

Author

Braga, Antonio, Lopes, Renata, Campos, Vanessa, Freitas, Fernanda, Maestá, Izildinha, Sun, Sue Yazaki, Pedrotti, Luana Giongo, Bessel, Marina, de Sousa, Christiani Bisinoto, Leal, Elaine, Yela, Daniela, Uberti, Elza, Madi, José Mauro, Viggiano, Mauricio, Junior, Joffre Amim, Filho, Jorge Rezende, Elias, Kevin M., Horowitz, Neil S., and Berkowitz, Ross S.

Published
2023
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47. High-Throughput Machine Learning from Electronic Health Records

Author

Kleiman, Ross S., Bennett, Paul S., Peissig, Peggy L., Berg, Richard L., Kuang, Zhaobin, Hebbring, Scott J., Caldwell, Michael D., and Page, David

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

The widespread digitization of patient data via electronic health records (EHRs) has created an unprecedented opportunity to use machine learning algorithms to better predict disease risk at the patient level. Although predictive models have previously been constructed for a few important diseases, such as breast cancer and myocardial infarction, we currently know very little about how accurately the risk for most diseases or events can be predicted, and how far in advance. Machine learning algorithms use training data rather than preprogrammed rules to make predictions and are well suited for the complex task of disease prediction. Although there are thousands of conditions and illnesses patients can encounter, no prior research simultaneously predicts risks for thousands of diagnosis codes and thereby establishes a comprehensive patient risk profile. Here we show that such pandiagnostic prediction is possible with a high level of performance across diagnosis codes. For the tasks of predicting diagnosis risks both 1 and 6 months in advance, we achieve average areas under the receiver operating characteristic curve (AUCs) of 0.803 and 0.758, respectively, across thousands of prediction tasks. Finally, our research contributes a new clinical prediction dataset in which researchers can explore how well a diagnosis can be predicted and what health factors are most useful for prediction. For the first time, we can get a much more complete picture of how well risks for thousands of different diagnosis codes can be predicted.

Published
2019

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