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Patients with obstructive sleep apnea are at great risk of flavor disorders: a 15-year population-based cohort study

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Clinical Oral Investigations 2023年第1期27卷 183-192页

作者： Huang, Hsin-Hsin Ma, Kevin Sheng-Kai Wu, Min-You Hung, Yao-Min Tsao, Chien-Han Wei, James Cheng-Chung Wen, Wei-Sheng Wang, Yu-Hsun Hung, Shih-Yen Chao, Max Min Center for Global Health Perelman School of Medicine University of Pennsylvania Philadelphia PA United States Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA United States Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering & Computer Science National Taiwan University Taipei Taiwan Institute of Medicine Chung Shan Medical University Taichung Taiwan Department of Emergency Medicine Kaohsiung Veterans General Hospital Kaohsiung Taiwan School of Medicine National Yang Ming University Taipei Taiwan Department of Otolaryngology Chung Shan Medical University Hospital Taichung Taiwan School of Medicine Chung Shan Medical University Taichung Taiwan Division of Allergy Immunology and Rheumatology Chung Shan Medical University Hospital Taichung Taiwan Graduate Institute of Integrated Medicine China Medical University Taichung Taiwan Department of Medical Research Chung Shan Medical University Hospital Taichung Taiwan Chi-Mei Medical Center Tainan Taiwan

Objective: Obstructive sleep apnea (OSA) results from upper airway remodeling, which has been suggested to alter sensory and motor neuron function due to hypoxia or snore vibration. This study investigated whether OSA was associated with the risk of flavor disorder (FD). Materials and methods: Seven thousand and eight hundred sixty-five patients with OSA and 7865 propensity score-matched controls without OSA were enrolled between 1999 and 2013 through a nationwide cohort study. The propensity score matching was based on age, sex, comorbidities including hypertension, hyperlipidemia, chronic obstructive pulmonary disease (COPD), asthma, ankylosing spondylitis, and Charlson comorbidity index, and co-medications during the study period, including statins and angiotensin-converting enzyme (ACE) inhibitors. The adjusted hazard ratio (aHR) of incident FD following OSA was derived using a Cox proportional hazard model. A log-rank test was used to evaluate the time-dependent effect of OSA on FD. Age, sex, comorbidities, and co-medications were stratified to identify subgroups susceptible to OSA-associated FD. Results: Patients with OSA were at a significantly great risk of FD (aHR = 1.91, 95% CI = 1.08–3.38), which was time-dependent (log-rank test p = 0.013). Likewise, patients with hyperlipidemia were at a significant great risk of FD (aHR = 2.99, 95% CI = 1.33–6.69). Subgroup analysis revealed that female patients with OSA were at higher risks of FD (aHR = 2.39, 95%CI = 1.05–5.47). Conclusions: Patients with OSA were at significantly great risk of incident FD during the 15-year follow-up period, especially in female patients with OSA. Clinical relevance: Timely interventions for OSA may prevent OSA-associated FD. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Flavor disorder Obstructive sleep apnea Population-based cohort study Smell disorder Taste disorder

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Growing from Exploration: A self-exploring framework for robots based on foundation models

arXiv

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arXiv 2024年

作者： Li, Shoujie Yu, Ran Wu, Tong Zhong, JunWen Zhang, Xiao-Ping Ding, Wenbo Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Physics and Chemistry Faculty of Science and Technology University of Macau Avenida da Universidade Taipa 999078 China Department of Electrical Computer and Biomedical Engineering Ryerson University TorontoONM5B 2K3 Canada RISC-V International Open Source Laboratory Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China

Intelligent robot is the ultimate goal in the robotics field. Existing works leverage learning-based or optimization-based methods to accomplish human-defined tasks. However, the challenge of enabling robots to explore various environments autonomously remains unresolved. In this work, we propose a framework named GExp, which enables robots to explore and learn autonomously without human intervention. To achieve this goal, we devise modules including self-exploration, knowledge-base-building, and close-loop feedback based on foundation models. Inspired by the way that infants interact with the world, GExp encourages robots to understand and explore the environment with a series of self-generated tasks. During the process of exploration, the robot will acquire skills from beneficial experiences that are useful in the future. GExp provides robots with the ability to solve complex tasks through self-exploration. GExp work is independent of prior interactive knowledge and human intervention, allowing it to adapt directly to different scenarios, unlike previous studies that provided in-context examples as few-shot learning. In addition, we propose a workflow of deploying the real-world robot system with self-learned skills as an embodied assistant. Project website: ***. © 2024, CC BY.

关键词： Intelligent robots

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Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch 22

Accelerating Real-Time Imaging for Radiotherapy: Leveraging ...

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22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023

作者： Obe, Ruth Kaufmann, Brandt Baird, Kaelen Kadel, Sam Soltani, Yasmin Cham, Mostafa Gobbert, Matthias K. Barajas, Carlos A. Jiang, Zhuoran Sharma, Vijay R. Ren, Lei Peterson, Stephen W. Poif, Jerimy C. U. of Houston-Clear Lake Dept. of Computer Science and of Software Engineering United States U. of San Francisco Dept. of Mathematics and Statistics United States Skidmore College Dept. of Computer Science and of Mathematics United States Mount Holyoke College Dept. of Computer Science and of Psychology United States U. of Houston Dept. of Biomedical Engineering United States U. of Maryland Dept. of Information Systems Baltimore County United States U. of Maryland Dept. of Mathematics and Statistics Baltimore County United States Medical Physics Graduate Program Duke University United States U. of Maryland School of Medicine Dept. of Radiation Oncology United States U. of Maryland School of Medicine Department of Radiation Oncology United States U. of Cape Town Dept. of Physics South Africa H3D Inc. United States

ISBN: (纸本)9798350345346

Proton beam therapy is an advanced form of cancer radiotherapy that uses high-energy proton beams to deliver precise and targeted radiation to tumors. This helps to mit-igate unnecessary radiation exposure in healthy tissues. Real-time imaging of prompt gamma rays with Compton cameras has been suggested to improve therapy efficacy. However, the camera's non-zero time resolution leads to incorrect interaction classifications and noisy images that are insufficient for accurately assessing proton delivery in patients. To address the challenges posed by the Compton camera's image quality, machine learning techniques are employed to classify and refine the generated data. These machine-learning techniques include recurrent and feedforward neural networks. A PyTorch model was designed to improve the data captured by the Compton camera. This decision was driven by PyTorch's flexibility, powerful capabilities in handling sequential data, and enhanced G PU usage. This accelerates the model's computations on large-scale radiotherapy data. Through hyperparameter tuning, the validation accuracy of our PyTorch model has been improved from an initial 7 % to over 60 %. Moreover, the PyTorch Distributed Data Parallelism strategy was used to train the RNN models on multiple G PU s, which significantly reduced the training time with a minor impact on model accuracy. © 2023 IEEE.

关键词： Clas-sification Compton camera Distributed Data Parallelism Proton beam therapy PyTorch Recurrent neural network

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Development of a Bioactive, Piezoelectric PVDF-TrFE Scaffold to Modulate Wound Response in the Peripheral Nervous System

SSRN

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SSRN 2024年

作者： Bryan, Andrew E. Krutko, Maksym Rebholz, Sandra Marquez, Lindsey E. Busch, Emma Dong, Kevin Pixley, Sarah K. Cushion, Melanie T. Esfandiari, Leyla Harris, Greg M. Department of Chemical and Environmental Engineering University of Cincinnati CincinnatiOH45221 United States Department of Biomedical Engineering University of Cincinnati CincinnatiOH45221 United States Department of Internal Medicine University of Cincinnati College of Medicine CincinnatiOH45267 United States Medical Research Service Cincinnati Veterans Affairs Medical Center CincinnatiOH45220 United States Department of Pharmacology and Systems Physiology University of Cincinnati College of Medicine CincinnatiOH45267 United States Department of Electrical Engineering University of Cincinnati CincinnatiOH45221 United States Department of Environmental & Public Health Sciences University of Cincinnati College of Medicine CincinnatiOH45267 United States Neuroscience Graduate Program University of Cincinnati College of Medicine CincinnatiOH45267 United States

To address current limitations in biomaterials for peripheral nerve repair regarding a lack of physiologically relevant signaling and immune response following implantation, this study evaluated the development and feasibility of a multi-cue biomaterial with physiologically relevant chemical, electrical, and physical signaling. To accomplish this, a bulk-functionalized poly(vinylidene fluoride-trifluoroethylene) (PVDF-TrFE) scaffold was fabricated using blend electrospinning to incorporate decellularized extracellular matrix (dECM) to mediate the foreign body response in vivo and promote enhanced wound healing. Decellularized ECM was secreted and assembled by fibroblast cells and incorporated into the electrospinning solution with concentration values ranging from 0% to 0.4% (m/v). Physical, chemical, and electrical properties of the scaffold were analyzed by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), X-ray diffractometry (XRD), mechanical tensile testing, and voltage readings for piezoelectricity. Blended scaffolds were evaluated in vitro for analysis of cell-material interactions in the context of peripheral nerve injury (PNI) repair and in vivo for immune response. In vitro work demonstrated increased cell metabolism and elongated, repair-like morphologies in Schwann cells on scaffolds with higher dECM concentrations. Subcutaneous implantation of blended scaffolds in rats at 7 days revealed limited multi-nucleated giant cell formation. Following 28 days in vivo, regenerative characteristics of the proliferative phase of wound healing were present with enhanced nerve growth and vasculature to scaffold. Overall, blend-electrospun scaffolds with native dECM showed promise in mitigating pro-inflammatory responses and promote advanced regenerative behaviors, thereby providing an implantable biomaterial with the necessary physical, chemical, and electrical characteristics desired for c

关键词： Fourier transform infrared spectroscopy

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Empowering biomedical Discovery with AI Agents

arXiv

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arXiv 2024年

作者： Gao, Shanghua Fang, Ada Huang, Yepeng Giunchiglia, Valentina Noori, Ayush Schwarz, Jonathan Richard Ektefaie, Yasha Kondic, Jovana Zitnik, Marinka Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Program in Biological and Biomedical Sciences Harvard Medical School BostonMA United States Department of Brain Sciences Imperial College London London United Kingdom Harvard College CambridgeMA United States Program in Biomedical Informatics Harvard Medical School BostonMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University MA United States Broad Institute of MIT and Harvard CambridgeMA United States Harvard Data Science Initiative CambridgeMA United States

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI’s ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies. © 2024, CC BY.

关键词： Adversarial machine learning

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Machine learning for improved current-density reconstruction from two-dimensional vector magnetic images

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Physical Review Applied 2025年第3期23卷 034035-034035页

作者： Niko R. Reed Danyal Bhutto Matthew J. Turner Declan M. Daly Sean M. Oliver Jiashen Tang Kevin S. Olsson Nicholas Langellier Mark J.H. Ku Department of Physics University of Maryland College Park Maryland USA Quantum Technology Center University of Maryland College Park Maryland USA Joint Quantum Institute University of Maryland College Park Maryland USA Department of Biomedical Engineering Boston University Boston Massachusetts USA A. A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown Massachusetts USA Department of Electrical and Computer Engineering University of Maryland College Park Maryland USA The MITRE Corporation McLean Virginia 22102 USA Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College Park Maryland 20742 USA Department of Physics Harvard University Cambridge Massachusetts USA Present address: VideaHealth Inc. Boston MA. Department of Materials Science and Engineering University of Delaware Newark Delaware 19716 USA Department of Physics and Astronomy University of Delaware Newark Delaware 19716 USA Present address: Northrop Grumman Mission Systems Linthicum Maryland 21090 USA.

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high-spatial-frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional images of vector magnetic fields acquired by a quantum diamond microscope . Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower-signal-to-noise-ratio data, significantly reducing the data collection time and permitting reconstructions of weaker and three-dimensional current sources.

关键词： Signal to noise ratio

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Terahertz Landau Polaritons in Nano-slots: Ultrastrong Coupling under Extreme Spatial Confinement

Terahertz Landau Polaritons in Nano-slots: Ultrastrong Coupl...

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International Conference on Infrared and Millimeter Waves

作者： Dasom Kim Sunghwan Kim Dukhyung Lee Shuang Liang Fuyang Tay Michael J. Manfra Dai-Sik Kim Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Physics Long-wavelength Nanotechnology Laboratory and Quantum Photonics Institute Ulsan National Institute of Science and Technology (UNIST) Ulsan South Korea Department of Physics and Astronomy Purdue University West Lafayette IN USA Birck Nanotechnology Center Purdue University West Lafayette IN USA Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Materials Engineering Purdue University West Lafayette IN USA Department of Physics and Astronomy Rice University Houston TX USA Department of Material Science and NanoEngineering Rice University Houston TX USA

We report ultrastrong coupling of the cyclotron resonance of a two-dimensional electron gas in a GaAs quantum well to terahertz cavity photons under extreme confinement to the nanometer scale. This was realized by an array of nano-slots fabricated close to the quantum well layer on the GaAs substrate. Our terahertz magnetospectroscopic measurements revealed two polariton branches as a function of applied magnetic field. While the photon-like part of the two polariton branches was clearly observed, the matter-like part was generally elusive. Our electromagnetic simulations quantitatively reproduce our observation for the upper-polariton branch. However, for the lower-polariton branch, our simulations predict a pronounced resonance, which was absent in experimental spectra. This discrepancy may be a consequence of the breakdown of the dipole approximation in this extreme confinement situation.

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Blue micro-LED with a red/green blended polymer film for 3.5-Gbps visible light communication employing adaptive SNR-Flattening Algorithm

Next Nanotechnology

引用

Next Nanotechnology 2024年 5卷

作者： Ho, Pin-Wei Cheng, Chih-Hsien Liao, Yu-Sheng Chi, Yu-Chieh Sadhu, Annada Sankar Matsumoto, Atsushi Akahane, Kouichi Chen, Li-Yin Kuo, Hao-Chung Lin, Gong-Ru Graduate Institute of Photonics and Optoelectronics and Department of Electrical Engineering National Taiwan University Taipei 106319 Taiwan National Institute of Information and Communications Technology Koganei Tokyo 184-8795 Japan SANWAY OPTOELECTRONICS TECH. CORP New Taipei City 235601 Taiwan Department of Photonics Institute of Electro-Optical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu 30010 Taiwan International Ph.D. Program in Photonics (UST) College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu 30010 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei 11492 Taiwan NTU-Tektronix Joint Research Center Tektronix Inc. and National Taiwan University Taipei 106319 Taiwan

By the semipolar blue single GaN μ-LED and blended Ir(piq)2(acac) + CC-MP5 polymer thin film color converter, a high-speed white-light μ-LED-based system is built up for the applications of short-distance VLC. The characteristics and properties of both devices are analyzed to understand the requirements for transmission and illumination. By selecting the growing orient, the influence of QCSE is reduced in this GaN μ-LED. Meanwhile, possessing the low reflection characteristic, it is beneficial for signal modulation. For the polymer thin film color converter with a lifetime of 7.8 ns, low surface reflection and high conversion efficiency are thought of good properties. Color-converted cool white light has a CCT of around 7000 K and high color accuracy with a CRI of about 90. The APD-combined frequency responses of the GaN μ-LED and GaN μ-LED + polymer are measured as 750 MHz and 600 MHz, respectively. After the optimization by utilizing the adaptive SNR-flattening pre-emphasis algorithm, the transmission performance of the white-light μ-LED is significantly promoted. For NRZ-OOK encoding, a 1.4 Gbps 0.15-m free-space transmission is achieved with a rising time of 656.33 ps, a falling time of 493.32 ps, and a Q-factor of 4.75. Besides, in more advanced data formats, the performance of this white-light μ-LED can be better highlighted. For the same 0.15-m free-space VLC, a high-speed 3 Gbps broadband 8-QAM-OFDM transmission is fulfilled with an EVM of 23.9%, an average SNR of 12.5, and a BER below 3.8 × 10^-3;while to the best of our knowledge, a record 3.5 Gbps BL-DMT transmission is implemented as well. This white-light μ-LED can also be integrated into large-scale arrays for multi-functional VLC applications. © 2024 The Authors

关键词： Adaptive SNR-Flattening algorithm Blue micro-LED Red/Green blended polymer Visible light communication

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Loss tangent fluctuations due to two-level systems in superconducting microwave resonators

arXiv

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arXiv 2024年

作者： Vallières, André Russell, Megan E. You, Xinyuan Garcia-Wetten, David A. Goronzy, Dominic P. Walker, Mitchell J. Bedzyk, Michael J. Hersam, Mark C. Romanenko, Alexander Lu, Yao Grassellino, Anna Koch, Jens McRae, Corey Rae H. Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Fermi National Accelerator Laboratory BataviaIL60510 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Center for Applied Physics and Superconducting Technologies Northwestern University EvanstonIL60208 United States Electrical Computing and Energy Engineering Department University of Colorado BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States National Institute of Standards and Technology BoulderCO80305 United States

Superconducting microwave resonators are critical to quantum computing and sensing technologies. Additionally, they are common proxies for superconducting qubits when determining the effects of performance-limiting loss mechanisms such as from two-level systems (TLS). The extraction of these loss mechanisms is often performed by measuring the internal quality factor Qi as a function of power or temperature. In this work, we investigate large temporal fluctuations of Qi at low powers over periods of 12 to 16 hours (relative standard deviation σQi/Qi = 13%). These fluctuations are ubiquitous across multiple resonators, chips and cooldowns. We are able to attribute these fluctuations to variations in the TLS loss tangent due to two main indicators. First, measured fluctuations decrease as power and temperature increase. Second, for interleaved measurements, we observe correlations between low- and medium-power Qi fluctuations and an absence of correlations with high-power fluctuations. Agreement with the TLS loss tangent mean is obtained by performing measurements over a time span of a few hours. We hypothesize that, in addition to decoherence due to coupling to individual near-resonant TLS, superconducting qubits are affected by these observed TLS loss tangent fluctuations. © 2024, CC BY.

关键词： Qubits

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Perspective—The Feasibility of Continuous Protein Monitoring in Interstitial Fluid

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ECS Sensors Plus 2023年第2期2卷 027001-027001页

作者： Young, Thomas Clark, Vincent Arroyo-Currás, Netzahualcóyotl Heikenfeld, Jason Department of Biomedical Engineering University of Cincinnati Cincinnati 45221 OH United States Chemistry-Biology Interface Program Zanvyl Krieger School of Arts & Sciences Johns Hopkins University Baltimore 21218 MD United States Department of Electrical & Computer Engineering University of Cincinnati Cincinnati 45221 OH United States Department of Pharmacology and Molecular Sciences Johns Hopkins University School of Medicine Baltimore 21205 MD United States

Highlights Continuous monitoring or sensing of proteins. Biological challenges to continuous sensors for proteins. Biosensor sensitivity, longevity, and antifouling are areas for future research. © 2023 The Autho...

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