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2. Kids rule

Author

Arif, Sameen and Chen, Luke Hsing-shu

Published
2022

3. SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module Accelerators

Author

Odema, Mohanad, Chen, Luke, Kwon, Hyoukjun, and Faruque, Mohammad Abdullah Al

Subjects
Computer Science - Hardware Architecture, Computer Science - Artificial Intelligence, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning, Computer Science - Performance
Abstract

Emerging multi-model workloads with heavy models like recent large language models significantly increased the compute and memory demands on hardware. To address such increasing demands, designing a scalable hardware architecture became a key problem. Among recent solutions, the 2.5D silicon interposer multi-chip module (MCM)-based AI accelerator has been actively explored as a promising scalable solution due to their significant benefits in the low engineering cost and composability. However, previous MCM accelerators are based on homogeneous architectures with fixed dataflow, which encounter major challenges from highly heterogeneous multi-model workloads due to their limited workload adaptivity. Therefore, in this work, we explore the opportunity in the heterogeneous dataflow MCM AI accelerators. We identify the scheduling of multi-model workload on heterogeneous dataflow MCM AI accelerator is an important and challenging problem due to its significance and scale, which reaches O(10^56) even for a two-model workload on 6x6 chiplets. We develop a set of heuristics to navigate the huge scheduling space and codify them into a scheduler, SCAR, with advanced techniques such as inter-chiplet pipelining. Our evaluation on ten multi-model workload scenarios for datacenter multitenancy and AR/VR use-cases has shown the efficacy of our approach, achieving on average 27.6% and 29.6% less energy-delay product (EDP) for the respective applications settings compared to homogeneous baselines., Comment: MICRO'24

Published
2024

4. Rosai-Dorfman-Destombes disease in adults: a single center experience

Author

Leung, Emily, Pryma, Collin, Murphy, Stephen, Harrison, Rebecca, Peterson, Erica, Tsang, Peter W. K., Varghese, Julia, You, Xiaotian (Julie), Slack, Graham W., Skinnider, Brian F., Ng, Tony, Young, Sean, Burrell, Steven, Stubbins, Ryan, Lim, Howard, Carruthers, Mollie, Dutz, Jan, Diamond, Eli L., and Chen, Luke Y. C.

Published
2024
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5. DOMINO: Domain-invariant Hyperdimensional Classification for Multi-Sensor Time Series Data

Author

Wang, Junyao, Chen, Luke, and Faruque, Mohammad Abdullah Al

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

With the rapid evolution of the Internet of Things, many real-world applications utilize heterogeneously connected sensors to capture time-series information. Edge-based machine learning (ML) methodologies are often employed to analyze locally collected data. However, a fundamental issue across data-driven ML approaches is distribution shift. It occurs when a model is deployed on a data distribution different from what it was trained on, and can substantially degrade model performance. Additionally, increasingly sophisticated deep neural networks (DNNs) have been proposed to capture spatial and temporal dependencies in multi-sensor time series data, requiring intensive computational resources beyond the capacity of today's edge devices. While brain-inspired hyperdimensional computing (HDC) has been introduced as a lightweight solution for edge-based learning, existing HDCs are also vulnerable to the distribution shift challenge. In this paper, we propose DOMINO, a novel HDC learning framework addressing the distribution shift problem in noisy multi-sensor time-series data. DOMINO leverages efficient and parallel matrix operations on high-dimensional space to dynamically identify and filter out domain-variant dimensions. Our evaluation on a wide range of multi-sensor time series classification tasks shows that DOMINO achieves on average 2.04% higher accuracy than state-of-the-art (SOTA) DNN-based domain generalization techniques, and delivers 16.34x faster training and 2.89x faster inference. More importantly, DOMINO performs notably better when learning from partially labeled and highly imbalanced data, providing 10.93x higher robustness against hardware noises than SOTA DNNs.

Published
2023

8. Romanus: Robust Task Offloading in Modular Multi-Sensor Autonomous Driving Systems

Author

Chen, Luke, Odema, Mohanad, and Faruque, Mohammad Abdullah Al

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Due to the high performance and safety requirements of self-driving applications, the complexity of modern autonomous driving systems (ADS) has been growing, instigating the need for more sophisticated hardware which could add to the energy footprint of the ADS platform. Addressing this, edge computing is poised to encompass self-driving applications, enabling the compute-intensive autonomy-related tasks to be offloaded for processing at compute-capable edge servers. Nonetheless, the intricate hardware architecture of ADS platforms, in addition to the stringent robustness demands, set forth complications for task offloading which are unique to autonomous driving. Hence, we present $ROMANUS$, a methodology for robust and efficient task offloading for modular ADS platforms with multi-sensor processing pipelines. Our methodology entails two phases: (i) the introduction of efficient offloading points along the execution path of the involved deep learning models, and (ii) the implementation of a runtime solution based on Deep Reinforcement Learning to adapt the operating mode according to variations in the perceived road scene complexity, network connectivity, and server load. Experiments on the object detection use case demonstrated that our approach is 14.99% more energy-efficient than pure local execution while achieving a 77.06% reduction in risky behavior from a robust-agnostic offloading baseline., Comment: This paper has been accepted to the 2022 International Conference On Computer-Aided Design (ICCAD 2022)

Published
2022
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9. Neural Contextual Bandits Based Dynamic Sensor Selection for Low-Power Body-Area Networks

Author

Demirel, Berken Utku, Chen, Luke, and Faruque, Mohammad Abdullah Al

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Providing health monitoring devices with machine intelligence is important for enabling automatic mobile healthcare applications. However, this brings additional challenges due to the resource scarcity of these devices. This work introduces a neural contextual bandits based dynamic sensor selection methodology for high-performance and resource-efficient body-area networks to realize next generation mobile health monitoring devices. The methodology utilizes contextual bandits to select the most informative sensor combinations during runtime and ignore redundant data for decreasing transmission and computing power in a body area network (BAN). The proposed method has been validated using one of the most common health monitoring applications: cardiac activity monitoring. Solutions from our proposed method are compared against those from related works in terms of classification performance and energy while considering the communication energy consumption. Our final solutions could reach $78.8\%$ AU-PRC on the PTB-XL ECG dataset for cardiac abnormality detection while decreasing the overall energy consumption and computational energy by $3.7 \times$ and $4.3 \times$, respectively., Comment: To be appeared at The International Symposium on Low Power Electronics and Design (ISLPED) 2022

Published
2022

10. Hardware Trojan Detection using Graph Neural Networks

Author

Yasaei, Rozhin, Chen, Luke, Yu, Shih-Yuan, and Faruque, Mohammad Abdullah Al

Subjects
Computer Science - Cryptography and Security, Computer Science - Hardware Architecture
Abstract

The globalization of the Integrated Circuit (IC) supply chain has moved most of the design, fabrication, and testing process from a single trusted entity to various untrusted third-party entities around the world. The risk of using untrusted third-Party Intellectual Property (3PIP) is the possibility for adversaries to insert malicious modifications known as Hardware Trojans (HTs). These HTs can compromise the integrity, deteriorate the performance, and deny the functionality of the intended design. Various HT detection methods have been proposed in the literature; however, many fall short due to their reliance on a golden reference circuit, a limited detection scope, the need for manual code review, or the inability to scale with large modern designs. We propose a novel golden reference-free HT detection method for both Register Transfer Level (RTL) and gate-level netlists by leveraging Graph Neural Networks (GNNs) to learn the behavior of the circuit through a Data Flow Graph (DFG) representation of the hardware design. We evaluate our model on a custom dataset by expanding the Trusthub HT benchmarks \cite{trusthub1}. The results demonstrate that our approach detects unknown HTs with 97% recall (true positive rate) very fast in 21.1ms for RTL and 84% recall in 13.42s for Gate-Level Netlist.

Published
2022

11. Feature Augmented Hybrid CNN for Stress Recognition Using Wrist-based Photoplethysmography Sensor

Author

Rashid, Nafiul, Chen, Luke, Dautta, Manik, Jimenez, Abel, Tseng, Peter, and Faruque, Mohammad Abdullah Al

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning
Abstract

Stress is a physiological state that hampers mental health and has serious consequences to physical health. Moreover, the COVID-19 pandemic has increased stress levels among people across the globe. Therefore, continuous monitoring and detection of stress are necessary. The recent advances in wearable devices have allowed the monitoring of several physiological signals related to stress. Among them, wrist-worn wearable devices like smartwatches are most popular due to their convenient usage. And the photoplethysmography (PPG) sensor is the most prevalent sensor in almost all consumer-grade wrist-worn smartwatches. Therefore, this paper focuses on using a wrist-based PPG sensor that collects Blood Volume Pulse (BVP) signals to detect stress which may be applicable for consumer-grade wristwatches. Moreover, state-of-the-art works have used either classical machine learning algorithms to detect stress using hand-crafted features or have used deep learning algorithms like Convolutional Neural Network (CNN) which automatically extracts features. This paper proposes a novel hybrid CNN (H-CNN) classifier that uses both the hand-crafted features and the automatically extracted features by CNN to detect stress using the BVP signal. Evaluation on the benchmark WESAD dataset shows that, for 3-class classification (Baseline vs. Stress vs. Amusement), our proposed H-CNN outperforms traditional classifiers and normal CNN by 5% and 7% accuracy, and 10% and 7% macro F1 score, respectively. Also for 2-class classification (Stress vs. Non-stress), our proposed H-CNN outperforms traditional classifiers and normal CNN by 3% and ~5% accuracy, and ~3% and ~7% macro F1 score, respectively., Comment: 4 pages, 3 figures, to be published in 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2021

Published
2021

15. Innovations en genomique pour les maladies non diagnostiquees: le syndrome VEXAS (vacuoles intracytoplasmiques dans les progeniteurs medu0laires, E1 ubiquitine ligase, liee a l'X, syndrome auto-inflammatoire, mutation somatique)

Author

Stubbins, Ryan J., Cherniawsky, Hannah, Chen, Luke Y.C., and Nevill, Thomas J.

Subjects
Genomics, Ligases, Health
Abstract

Tout au long de l'histoire de la medecine, les progres technologiques ont permis aux medecins de comprendre et de diagnostiquer des syndromes qui autrefois demeuraient des enigmes. Bien qu'Hippocrate decrivait [...]

Published
2022
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20. CRP and sCD25 help distinguish between adult‐onset Still's disease and HLH.

Author

Beckett, Madelaine, Spaner, Caroline, Goubran, Mariam, Wade, John, Avina‐Zubieta, Juan Antonio, Setiadi, Audi, Tucker, Lori, Shojania, Kam, Au, Sheila, Mattman, Andre, Lee, Agnes Y. Y., Fajgenbaum, David C., and Chen, Luke Y. C.

Subjects
STILL'S disease, CYTOKINE release syndrome, HEMOPHAGOCYTIC lymphohistiocytosis, MACROPHAGE activation, RECEIVER operating characteristic curves
Abstract

Objective: Adult‐onset Still's disease (AOSD) and secondary hemophagocytic lymphohistiocytosis (sHLH) are both hyperferritinemic cytokine storm syndromes that can be difficult to distinguish from each other in hospitalized patients. The objective of this study was to compare the inflammatory markers ferritin, D‐dimer, C‐reactive protein (CRP), and soluble CD25 (sCD25) in patients with AOSD and sHLH. These four markers were chosen as they are widely available and represent different aspects of inflammatory diseases: macrophage activation (ferritin); endothelialopathy (D‐dimer); interleukin‐1/interleukin‐6/tumour necrosis factor elevation (CRP) and T cell activation (sCD25). Methods: This was a single‐center retrospective study. Patients diagnosed by the Hematology service at Vancouver General Hospital for AOSD or sHLH from 2009 to 2023 were included. Results: There were 16 AOSD and 44 sHLH patients identified. Ferritin was lower in AOSD than HLH (median 11 360 μg/L vs. 29 020 μg/L, p =.01) while D‐dimer was not significantly different (median 5310 mg/L FEU vs. 7000 mg/L FEU, p =.3). CRP was higher (median 168 mg/L vs. 71 mg/L, p <.01) and sCD25 was lower (median 2220 vs. 7280 U/mL, p =.004) in AOSD compared to HLH. The combined ROC curve using CRP >130 mg/L and sCD25< 3900 U/mL to distinguish AOSD from HLH had an area under the curve (AUC) of 0.94 (95% confidence interval 0.93–0.97) with sensitivity 91% and specificity 93%. Conclusions: These findings suggest that simple, widely available laboratory tests such as CRP and sCD25 can help clinicians distinguish AOSD from HLH in acutely ill adults with extreme hyperferritinemia. Larger studies examining a wider range of clinically available inflammatory biomarkers in a more diverse set of cytokine storm syndromes are warranted. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Case 30-2024: A 45-Year-Old Woman with Kidney Lesions and Lytic Bone Disease.

Author

Chen, Luke Y. C., Huang, Ambrose J., Stone, John H., and Ferry, Judith A.

Subjects
*PLASMA cell diseases, *MEDICAL societies, *HIV infections, *SARCOIDOSIS, *CASTLEMAN'S disease, *SJOGREN'S syndrome
Abstract

This article presents a case study of a 45-year-old woman with kidney lesions and lytic bone disease. The patient underwent various imaging tests and reported symptoms such as fatigue and pain in the left shoulder and arm. Further evaluation and testing revealed polyclonal hypergammaglobulinemia with an elevated IgG level. The article explores potential causes for the patient's symptoms, ruling out certain diseases and suggesting a histiocytic disorder as the most likely diagnosis. Treatment options for systemic Rosai-Dorfman-Destombes disease are also discussed, with the patient in the case having a complete clinical response to cobimetinib. [Extracted from the article]

Published
2024
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22. An Electrosynthesis of 1,3,4‐Oxadiazoles from N‐Acyl Hydrazones.

Author

Chen, Luke, Thompson, James D. F., and Jamieson, Craig

Abstract

The 1,3,4‐oxadiazole is a widely encountered motif in the areas of pharmaceuticals, materials, and agrochemicals. This work has established a mediated electrochemical synthesis of 2,5‐disubstituted 1,3,4‐oxadiazoles from N‐acyl hydrazones. Using DABCO as the optimal redox mediator has enabled a mild oxidative cyclisation, without recourse to stoichiometric oxidants. In contrast to previous methods, this indirect electrochemical oxidation has enabled a broad range of substrates to be accessed, with yields of up to 83 %, and on gram scale. The simplicity of the method has been further demonstrated by the development of a one‐pot procedure, directly transforming readily available aldehydes and hydrazides into valuable heterocycles. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Machine Learning Techniques for Low-Power Mobile Health Systems

Author

Chen, Luke

Subjects
Computer engineering
Abstract

With ever-growing interests in personalized physical and mental healthcare, especially with the recent COVID-19 pandemic, along with the proliferation of applied machine learning (ML), automated health monitoring and prognosis using wearable devices with ML algorithms are increasingly more relevant. However, modern deep learning (DL) frameworks with state-of-the-art performances are unable to meet the memory and energy constraints of wearable devices. As such, there is a need for the design of efficient and effective ML models that can operate on these constrained devices while still achieving acceptable performance thresholds. This thesis presents two methodologies for effective and efficient ML under the wearable device setting, specifically a feature-augmented hybrid convolutional neural network architecture for stress monitoring using a wrist-based photoplethysmography sensor and a neural contextual-bandits-based dynamic sensor selection framework for cardiovascular disease detection with body-area-network of electrocardiogram sensor. Through extensive empirical studies, we find that our methods satisfy the constrained device settings while maintaining task performance and in some cases outperforming related ML and deep learning works. Additionally, we performed feasibility analysis on real embedded micro-controller hardware where run-time memory and energy profiling was measured and reported.

Published
2023

24. IgG4-Related Disease as Mimicker of Malignancy

Author

Zhou, WanLi, Murray, Timothy, Cartagena, Liliana, Lim, Howard, Schaeffer, David F., Slack, Graham W., Skinnider, Brian F., Lam, Eric, Irvine, Robert, Chung, Stephen, Mattman, Andre, Chang, Silvia D., Carruthers, Mollie N., and Chen, Luke Y. C.

Published
2021
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25. Innovations in genomics for undiagnosed diseases: vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome

Author

Stubbins, Ryan J., Cherniawsky, Hannah, Chen, Luke Y.C., and Nevill, Thomas J.

Subjects
Genomics -- Methods -- Forecasts and trends, Medical genetics -- Methods -- Forecasts and trends, Autoimmune diseases -- Diagnosis -- Genetic aspects, Market trend/market analysis, Health
Abstract

Throughout the history of medicine, technological progress has enabled physicians to understand and diagnose previously enigmatic syndromes. Although Hippocrates described many of the features of tuberculosis, it was not until [...]

Published
2022
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27. Sarilumab in patients admitted to hospital with severe or critical COVID-19: a randomised, double-blind, placebo-controlled, phase 3 trial

Author

Bazzalo, Ignacio J., Casas, Marcelo M., Nuñez, Sebastián A., Pere, Yael, Ibarrola, Carlos M., Solis Aramayo, Marco A., Cuesta, Maria C., Duarte, Andrea E., Gutierrez Fernandez, Pablo M., Iannantuono, Maria A., Miyazaki, Erica A., Silvio, Javier P., Scublinsky, Dario G., Bales, Alessandra, Catarino, Daniela, Fiss, Elie, Mohrbacher, Sara, Sato, Victor, Baylao, Antonio, Cavalcante, Adilson, Correa, Francini, de Andrade, Celso A., Furtado, Juvencio, Ribeiro Filho, Nelson, Telles, Valéria, Trevelin, Leopoldo T., Vipich, Ricardo, Boldo, Rodrigo, Borges, Paula, Lobo, Suzana, Luckemeyer, Graziela, Machado, Luana, Alves, Maysa B., Iglessias, Ana C., Lago, Marianna M., Santos, Daniel W., Chapdelaine, Hugo, Falcone, Emilia L., Jamal, Rahima, Luong, Me-Linh, Durand, Madeleine, Doucet, Stephane, Carrier, François-Martin, Coburn, Bryan A., Del Sorbo, Lorenzo, Walmsley, Sharon L., Belga, Sara, Chen, Luke Y., Mah, Allison D., Steiner, Theodore, Wright, Alissa J., Hajek, J., Adhikari, Neill, Fowler, Robert A., Daneman, Nick, Khwaja, Kosar A., Shahin, Jason, Gonzalez, Carolina, Silva, Rafael, Lindh, Marcelo, Maluenda, Gabriel, Fernandez, Patricia, Oyonarte, Maite, Lasso, Martin, Boyer, Alexandre, Bronnimann, Didier, Bui, Hoang-Nam, Cazanave, Charles, Chaussade, Helene, Desclaux, Arnaud, Ducours, Mailys, Duvignaud, Alexandre, Malvy, Denis, Martin, Lisa, Neau, Didier, Nguyen, Duc, Pistone, Thierry, Soubrane-Wirth, Gaetane, Leitao, Julie, Allavena, Clotilde, Biron, Charlotte, Bouchez, Sabelline, Gaborit, Benjamin, Gregoire, Antoine, Le Turnier, Paul, Lecompte, Anne-Sophie, Lecomte, Raphael, Lefebvre, Maeva, Raffi, Francois, Boutoille, David, Morineau, Pascale H., Guéry, Romain, Chatelus, Emmanuel, Dumoussaud, Nathalie, Felten, Renaud, Luca, Florina, Goichot, Bernard, Schneider, Francis, Taquet, Marie-Caroline, Groh, Matthieu, Roumier, Mathilde, Neuville, Mathilde, Bachelard, Antoine, Isernia, Valentina, Lescure, F-Xavier, Phung, Bao-Chau, Rachline, Anne, Sautereau, Aurelie, Vallois, Dorothee, Bleher, Yves, Boucher, Delphine, Coudon, Clémentine, Esnault, Jean, Guimard, Thomas, Leautez-Nainville, Sophie, Merrien, Dominique, Morrier, Marine, Motte-Vincent, Pauline, Gabeff, Romain, Leclerc, Hélène, Cozic, Céline, Decours, Romain, Février, Ronan, Colin, Gwenhael, Abgrall, Sophie, Vignes, Dorothee, Sterpu, Raluca, Kuellmar, Mira, Meersch-Dini, Melanie, Weiss, Raphael, Zarbock, Alexander, Antony, Christiane, Berger, Marc, Brenner, Thorsten, Taube, Christian, Herbstreit, Frank, Dolff, Sebastian, Konik, Margarethe, Schmidt, Karsten, Zettler, Markus, Witzke, Oliver, Boell, Boris, Garcia Borrega, Jorge, Koehler, Philipp, Zander, Thomas, Dusse, Fabian, Al-Sawaf, Othman, Köhler, Philipp, Eichenauer, Dennis, Kochanek, Matthias, Shimabukuro-Vornhagen, Alexander, Mellinghoff, Sibylle, Claßen, Annika, Heger, Jan-Michel, Meyer-Schwickerath, Charlotte, Liedgens, Paul, Heindel, Katrin, Belkin, Ana, Biber, Asaf, Gilboa, Mayan, Levy, Itzchak, Litachevsky, Vladislav, Rahav, Galia, Finesod Wiedner, Anat, Zilberman-Daniels, Tal, Oster, Yonatan, Strahilevitz, Jacob, Sviri, Sigal, Baldissera, Elena M., Campochiaro, Corrado, Cavalli, Giulio, Dagna, Lorenzo, De Luca, Giacomo, Della Torre, Emanuel, Tomelleri, Alessandro, Bernasconi De Luca, Davide, Capetti, Amedeo F., Coen, Massimo, Cossu, Maria V., Galli, Massimo, Giacomelli, Andrea, Gubertini, Guido A., Rusconi, Stefano, Burastero, Giulia J., Digaetano, Margherita, Guaraldi, Giovanni, Meschiari, Marianna, Mussini, Cristina, Puzzolante, Cinzia, Volpi, Sara, Aiello, Marina, Ariani, Alarico, Chetta, Alfredo A., Frizzelli, Annalisa, Ticinesi, Andrea, Tuttolomondo, Domenico, Aliberti, Stefano, Blasi, Francesco B., Di Pasquale, Marta F., Misuraca, Sofia, Pilocane, Tommaso, Simonetta, Edoardo, Aghelmo, Alessio M., Angelini, Claudio, Brunetta, Enrico, Canonica, Giorgio W., Ciccarelli, Michele, Dal Farra, Sara, De Santis, Maria, Ferri, Sebastian, Folci, Marco, Guidelli, Giacomo M., Heffler, Enrico M., Loiacono, Ferdinando, Malipiero, Giacomo, Paoletti, Giovanni, Pedale, Rosa, Puggioni, Francesca A., Racca, Francesca, Zumbo, Aurora, Satou, Morihiko, Honda, Hitoshi, Lisun, Tatyana, Protsenko, Denis, Rubtsov, Nikolay, Beloglazova, Irina, Fomina, Daria, Lysenko, Mariana, Serdotetskova, Sofia, Firstov, Vitali, Gordeev, Ivan, Kokorin, Ilia, Komissarova, Ksenia, Lapochkina, Nina, Luchinkina, Elena, Malimon, Valentin, Mamedguseyinova, Sevinch, Polubatonova, Ksenia, Suvorova, Natalia, Arribas, Jose, Borobia Perez, Alberto M., de la Calle Prieto, Fernando, Figueira, Juan Carlos, Motejano Sanchez, Rocio, Mora-Rillo, Marta, Prados Sanchez, Concepcion, Queiruga Parada, Javier, Fernandez Arnalich, Francisco, Guerro Barrientos, Maria, Bendala Estrada, Alejandro, Caballero Marcos, Aranzazu, Garcia Leoni, Maria E., García-Martínez, Rita, Collado, Ana María, Munoz Garcia, Patricia, Torres do Rego, Ana, Villalba García, María V., Burrillo, Almudena, Valerio Minero, Maricela, Gijon Vidaurreta, Paloma, Infante Herrero, Sonsoles, Velilla, Elena, Machado, Marina, Olmedo, Maria, Pinilla, Blanca, Almirante Gragera, Benito, Cañas Ruano, Maria de la Esperanza, Contreras Medina, Sofia, Cortés Herrera, Alejandro, Falcó Ferrer, Vicenç, Ferrer Roca, Ricard, Nuvials Casals, Xavier, Ribera Pascuet, Esteve, Suanzes Diez, Paula, Rebollo Castro, Pedro, Garcia Alcaide, Felipe, Soriano, Alejandro, Oliver Caldes, Aina, González Cordón, Ana, Cardozo, Celia, De la Mora Cañizo, Lorena, Pena López, Romina, Chamorro, Sandra, Crespillo-Andujar, Clara, Escudero Sanchez, Rosa, Fortún-Abete, Jesús, Monge-Maillo, Begoña, Moreno Zamora, Ana, Norman, Francesca, Sanchez Conde, Matilde, Serrano Villar, Sergio, Vizcarra, Pilar, Lescure, François-Xavier, Fowler, Robert A, Lazar, Jennifer Sloane, Shi, Genming, Wung, Peter, Patel, Naimish, and Hagino, Owen

Published
2021
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28. Molecular Alterations Associated with Histologically Overt Stromal Response in Patients with Prostate Cancer.

Author

Sayan, Mutlay, Tuac, Yetkin, Akgul, Mahmut, Kucukcolak, Samet, Tjio, Elza, Akbulut, Dilara, Chen, Luke W., Yang, David D., Moningi, Shalini, Leeman, Jonathan E., Orio, Peter F., Nguyen, Paul L., D'Amico, Anthony V., and Aktan, Cagdas

Subjects
PROSTATE cancer patients, RADICAL prostatectomy, GENE expression, PROGNOSIS, CELL division
Abstract

Prostate cancer has substantial heterogeneity in clinical outcomes and therapeutic responses, posing challenges in predicting disease progression and tailoring treatment strategies. Recent studies have highlighted the potential prognostic value of evaluating the tumor microenvironment, including the presence of a histologically overt stromal response (HOST-response) characterized by peri-glandular stromal changes and architectural distortions. This retrospective study examined patient records from The Cancer Genome Atlas database to identify genomic alterations associated with the HOST-response in prostate cancer. Among 348 patients who underwent radical prostatectomy, 160 (45.98%) were identified as having a HOST-response. A gene expression analysis revealed 1263 genes with significantly higher expression in patients with a HOST-response. A protein–protein interaction network analysis identified seven hub genes (KIF2C, CENPA, CDC20, UBE2C, ESPL1, KIF23, and PLK1) highly interconnected in the network. A functional enrichment analysis revealed alterations in the cell division, cytoskeletal organization, cytokinesis, and interleukin-16 signaling pathways in patients with a HOST-response, suggesting dysregulated proliferation and inflammation. The distinct molecular signature associated with the HOST-response provides insights into the tumor–stroma interactions driving adverse outcomes and potential targets for tailored therapeutic interventions in this subset of patients with prostate cancer. [ABSTRACT FROM AUTHOR]

Published
2024
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34. The neuro-otology of Susac syndrome

Author

Hardy, Todd A., Taylor, Rachael L., Qiu, Jessica, O’Brien, Billy, Gopinath, Sumana, Trewin, Benjamin, Spring, Penelope J., Shaffi, Mohamed, Bolitho, Sam J., Garsia, Roger J., Roxburgh, Richard, Mason, Deborah F., Ip, Jerome, Chan, Fiona, Chen, Luke, Wilson, Ian, Beadnall, Heidi N., Barnett, Michael H., Parratt, John D. E., Watson, John D. G., Welgampola, Miriam S., Reddel, Stephen W., Tsang, Benjamin, and Halmagyi, G. Michael

Published
2020
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38. A 52-Year-Old Woman With Dysarthria, Ataxia, Xanthelasmas, and Miliary Pulmonary Nodules.

Author

Huynh, Athena, Pryma, Collin, McPhaden, Heather, Yared, Karl-Christopher, Zhang, Yilin, Beadon, Katie, Ng, Tony, and Chen, Luke Y.C.

Subjects
PULMONARY nodules, DYSARTHRIA, ATAXIA, LUNG diseases, FRONTAL lobe, MENINGEAL cancer
Abstract

A 52-year-old woman with no significant medical history was referred to our hospital for expedited workup of progressive dysarthria and ataxia over the past year. Prior CT angiography of the head and neck showed no relevant neurologic findings but did reveal miliary lesions in the lung apices, which was later confirmed via dedicated CT chest scan (Fig 1). Review of systems was negative for any respiratory, constitutional, or rheumatologic symptoms, except for new xanthelasma-like lesions over her forehead. She previously had smoked with 20 pack-years and had no TB risk factors. MRI of the face showed a 21-mm mass within the left external temporal fascia. MRI of the head showed diffuse leptomeningeal enhancement, right frontal lobe enhancement, and cerebellar and brainstem T2/fluid-attenuated inversion recovery hyperintensity, which prompted her admission to hospital. [ABSTRACT FROM AUTHOR]

Published
2024
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39. 2519. A Multi-national Phase 3, Randomized, Double-Blind, Active Comparator-Controlled Clinical Trial to Study the Safety, Tolerability, and Efficacy of Imipenem/Cilastatin/Relebactam (MK-7655A) Versus Piperacillin/Tazobactam in Subjects with Hospital-Acquired Bacterial Pneumonia or Ventilator-Associated Bacterial Pneumonia

Author

Li, Junjie, primary, Wei, Feng, additional, Xiang, Peng, additional, Tang, Zhengang, additional, Ding, Lianshu, additional, Losada, Maria C, additional, Iamboliyska, Zlatka, additional, Zhu, Mingfen, additional, Guo, Xiaodan, additional, Du, Xiaoling, additional, Chen, Chang, additional, Chen, Luke Francis, additional, Zhou, Min, additional, and Qu, Jieming, additional

Published
2023
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42. Pharmacokinetics, Safety, and Tolerability of Imipenem/Cilastatin/Relebactam in Children with Confirmed or Suspected Gram‐Negative Bacterial Infections: A Phase 1b, Open‐Label, Single‐Dose Clinical Trial

Author

Bradley, John S., primary, Makieieva, Nataliia, additional, Tøndel, Camilla, additional, Roilides, Emmanuel, additional, Kelly, Matthew S., additional, Patel, Munjal, additional, Vaddady, Pavan, additional, Maniar, Alok, additional, Zhang, Ying, additional, Paschke, Amanda, additional, and Chen, Luke F., additional

Published
2023
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43. Effectiveness of targeted enhanced terminal room disinfection on hospital-wide acquisition and infection with multidrug-resistant organisms and Clostridium difficile: a secondary analysis of a multicentre cluster randomised controlled trial with crossover design (BETR Disinfection)

Author

Anderson, Deverick J, Moehring, Rebekah W, Weber, David J, Lewis, Sarah S, Chen, Luke F, Schwab, J Conrad, Becherer, Paul, Blocker, Michael, Triplett, Patricia F, Knelson, Lauren P, Lokhnygina, Yuliya, Rutala, William A, and Sexton, Daniel J

Published
2018
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46. Two-Phase Hospital-Associated Outbreak of Mycobacterium abscessus: Investigation and Mitigation

Author

Baker, Arthur W., Lewis, Sarah S., Alexander, Barbara D., Chen, Luke F., Wallace, Richard J., Brown-Elliott, Barbara A., Isaacs, Pamela J., Pickett, Lisa C., Patel, Chetan B., Smith, Peter K., Reynolds, John M., Engel, Jill, Wolfe, Cameron R., Milano, Carmelo A., Schroder, Jacob N., Davis, Robert D., Hartwig, Matthew G., Stout, Jason E., Strittholt, Nancy, Maziarz, Eileen K., Saullo, Jennifer Horan, Hazen, Kevin C., Walczak, Richard J., Vasireddy, Ravikiran, Vasireddy, Sruthi, McKnight, Celeste M., Anderson, Deverick J., and Sexton, Daniel J.

Published
2017

49. An intronic GAA repeat expansion in FGF14 causes the autosomal-dominant adult-onset ataxia SCA27B/ATX-FGF14

Author

Rafehi, Haloom, primary, Read, Justin, additional, Szmulewicz, David J., additional, Davies, Kayli C., additional, Snell, Penny, additional, Fearnley, Liam G., additional, Scott, Liam, additional, Thomsen, Mirja, additional, Gillies, Greta, additional, Pope, Kate, additional, Bennett, Mark F., additional, Munro, Jacob E., additional, Ngo, Kathie J., additional, Chen, Luke, additional, Wallis, Mathew J., additional, Butler, Ernest G., additional, Kumar, Kishore R., additional, Wu, Kathy HC., additional, Tomlinson, Susan E., additional, Tisch, Stephen, additional, Malhotra, Abhishek, additional, Lee-Archer, Matthew, additional, Dolzhenko, Egor, additional, Eberle, Michael A., additional, Roberts, Leslie J., additional, Fogel, Brent L., additional, Brüggemann, Norbert, additional, Lohmann, Katja, additional, Delatycki, Martin B., additional, Bahlo, Melanie, additional, and Lockhart, Paul J., additional

Published
2023
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