237 results on '"physiological modeling"'
Search Results
2. Projection of future heat-related morbidity in three metropolitan prefectures of Japan based on large ensemble simulations of climate change under 2 °C global warming scenarios
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Ueta, Haruto, Kodera, Sachiko, Sugimoto, Shiori, and Hirata, Akimasa
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- 2024
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Catalog
3. Towards Human-Centric Manufacturing: Exploring the Role of Human Digital Twins in Industry 5.0.
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Bucci, Ilaria, Fani, Virginia, and Bandinelli, Romeo
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Human-centricity, a cornerstone of Industry 5.0, emphasizes the central role of human needs and capabilities in the technological landscape of modern manufacturing. As Digital Twins (DTs) become a core technology of Industry 4.0, the evolution towards Human Digital Twins (HDTs) marks a significant shift to enhance human-system integration. HDTs serve as digital replicas that mirror human characteristics directly in system design and performance, facilitating a more nuanced approach to smart manufacturing. This paper addresses the critical need for deeper investigation into HDTs to fully leverage their potential in promoting human-centric manufacturing. Through a comprehensive review, the current state and rapid evolution of HDT frameworks and architectures within Industry 5.0 settings are explored. The enabling technologies that underpin HDTs, their applications across various industrial scenarios, and the challenges in their development are discussed. The analysis not only underscores the importance of HDTs in meeting the diverse needs of workers but also outlines future research directions to further empower individuals within the adaptive and intelligent manufacturing systems shaped by Industry 5.0. [ABSTRACT FROM AUTHOR] more...
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- 2025
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4. Advances in automated anesthesia: a comprehensive review
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Xiuding Cai, Xueyao Wang, Yaoyao Zhu, Yu Yao, and Jiao Chen
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Automatic Anesthesia ,Physiological Modeling ,Closed-loop Anesthesia Control ,Anesthesiology ,RD78.3-87.3 - Abstract
Abstract Anesthesia is a fundamental aspect of modern medical practice, ensuring patient safety and comfort during surgical procedures by effectively managing hypnosis and analgesia. The rapid advancement of artificial intelligence (AI) has facilitated the emergence of automated anesthesia systems, significantly enhancing the precision, efficiency, and adaptability of anesthesia management in complex surgical environments. This review provides a comprehensive survey of the existing literature on automated anesthesia, focusing on three key areas: physiological modeling, automatic anesthesia control, and performance evaluation. It critically examines the strengths and limitations of current methodologies, including traditional statistical learning, machine learning and deep learning approaches, while discussing future development trends in the field. By synthesizing recent technological advancements and clinical applications, this work aims to provide valuable insights for researchers and clinicians, promoting the evolution of intelligent and automated anesthesia practices. Ultimately, this review underscores the transformative potential of AI-driven solutions in delivering personalized anesthesia care, optimizing both hypnosis and analgesia, and enhancing surgical outcomes. more...
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- 2025
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5. Advances in automated anesthesia: a comprehensive review.
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Cai, Xiuding, Wang, Xueyao, Zhu, Yaoyao, Yao, Yu, and Chen, Jiao
- Abstract
Anesthesia is a fundamental aspect of modern medical practice, ensuring patient safety and comfort during surgical procedures by effectively managing hypnosis and analgesia. The rapid advancement of artificial intelligence (AI) has facilitated the emergence of automated anesthesia systems, significantly enhancing the precision, efficiency, and adaptability of anesthesia management in complex surgical environments. This review provides a comprehensive survey of the existing literature on automated anesthesia, focusing on three key areas: physiological modeling, automatic anesthesia control, and performance evaluation. It critically examines the strengths and limitations of current methodologies, including traditional statistical learning, machine learning and deep learning approaches, while discussing future development trends in the field. By synthesizing recent technological advancements and clinical applications, this work aims to provide valuable insights for researchers and clinicians, promoting the evolution of intelligent and automated anesthesia practices. Ultimately, this review underscores the transformative potential of AI-driven solutions in delivering personalized anesthesia care, optimizing both hypnosis and analgesia, and enhancing surgical outcomes. [ABSTRACT FROM AUTHOR] more...
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- 2025
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6. Exponential Functions Permit Estimation of Anaerobic Work Capacity and Critical Power from Less than 2 Min All-Out Test.
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Tsai, Ming-Chang, Thomas, Scott, and Klimstra, Marc
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ANAEROBIC capacity , *EXPONENTIAL functions , *LINEAR statistical models , *EXERCISE tests , *PHYSIOLOGICAL models - Abstract
The Critical Power Model (CPM) is key for assessing athletes' aerobic and anaerobic energy systems but typically involves lengthy, exhausting protocols. The 3 min all-out test (3MT) simplifies CPM assessment, yet its duration remains demanding. Exponential decay models, specifically mono- and bi-exponential functions, offer a more efficient alternative by accurately capturing the nonlinear energy dynamics in high-intensity efforts. This study explores shortening the 3MT using these functions to reduce athlete strain while preserving the accuracy of critical power (CP) and work capacity ( W ′ ) estimates. Seventy-six competitive cyclists and triathletes completed a 3MT on a cycle ergometer, with CP and W ′ calculated at shorter intervals. Results showed that a 90 s test using the bi-exponential model yielded CP and W ′ values similar to those of the full 3MT. Meanwhile, the mono-exponential model required at least 135 s. Bland–Altman and linear regression analyses confirmed that a 120 s test with the mono-exponential model reliably estimated CP and W ′ with minimal physical strain. These findings support a shortened, less-demanding 3MT as a valid alternative for CPM assessment. [ABSTRACT FROM AUTHOR] more...
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- 2024
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7. Functional Exercise Induces Adaptations in Muscle Oxygen Saturation in Division One Collegiate Butterfly Swimmers: A Randomized Controlled Trial.
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Grotke, Jack, Alcantara, Austin, Amitrano, Joe, and Seshadri, Dhruv R.
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OXYGEN saturation ,NEAR infrared spectroscopy ,SKIN diving ,EXERCISE therapy ,SHOULDER exercises ,SPORTS medicine - Abstract
This study investigates the impact of a five-week functional exercise intervention designed to enhance the muscular endurance of the posterior shoulder musculature, aiming to mitigate shoulder fatigue and overuse injury. Twelve Division I collegiate butterfly swimmers were recruited and evenly randomized into exercise (EX) and control (CTRL) groups. Weekly 100-yard butterfly sprints were performed, with Muscle Oxygen Saturation (SmO
2 ) continuously monitored using a wearable near-infrared spectroscopy (NIRS) device. This study is among the first to utilize wearable NIRS devices to monitor SmO2 underwater during swimming, demonstrating that a targeted 5-week exercise program significantly improves posterior shoulder endurance, as evidenced by increased Posterior Shoulder Endurance Test (PSET) scores and distinctive SmO2 adaptations in the EX-group compared to the CTRL group. These findings suggest that targeted dryland exercises can enhance posterior shoulder endurance with long-term implications for potentially reducing injury risk and improving performance. [ABSTRACT FROM AUTHOR] more...- Published
- 2024
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8. Modeling the renoprotective mechanisms of SGLT2 inhibition in hypertensive chronic kidney disease.
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Clemmer, John S., Yen, Timothy E., and Obi, Yoshitsugu
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CHRONIC kidney failure , *SODIUM-glucose cotransporters , *KIDNEY diseases , *GLOMERULAR filtration rate , *SODIUM-glucose cotransporter 2 inhibitors , *HYPERTENSION - Abstract
Sodium‐glucose cotransporter (SGLT)‐2 inhibitors have recently been approved for chronic kidney disease (CKD) based on their ability to lower proteinuria and slow CKD progression independent of diabetes status. In diabetic renal disease, modulation of tubuloglomerular feedback (TGF) leading to lower intraglomerular pressure has been postulated as one of the mechanisms of renal protection with SGLT2 inhibition; however, this mechanism has not been sufficiently explored in non‐diabetic CKD. We hypothesized that SGLT2 inhibition exerts renoprotection in CKD through increasing TGF despite normoglycemia. To test this hypothesis, we used an integrative mathematical model of human physiology, HumMod. Stage 3 CKD conditions were simulated by reducing nephron mass which was associated with hypertension, low glomerular filtration rate (GFR) (55 mL/min), hyperfiltration of remnant nephrons, elevated albuminuria (500 mg/day), and minimal levels of urinary glucose (0.02 mmol/L). SGLT2 inhibition was associated with acute reductions in GFR associated with afferent arteriolar vasoconstriction due to TGF. After 12 months, glomerular pressure, nephron damage, and chronic GFR decline were reduced with SGLT2 inhibition with additional SGLT1 inhibitory effects further enhancing these effects. This model supports the use of SGLT2 inhibitors to reduce hyperfiltration in CKD and mitigate renal disease progression, even in the absence of diabetes. [ABSTRACT FROM AUTHOR] more...
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- 2023
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9. Dynamic fluctuations in ascending heart-to-brain communication under mental stress.
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Candia-Rivera, Diego, Norouzi, Kian, Ramsøy, Thomas Zoëga, and Valenza, Gaetano
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AUTONOMIC nervous system , *PHYSIOLOGICAL stress , *CENTRAL nervous system - Abstract
Dynamical information exchange between central and autonomic nervous systems, as referred to functional brain-heart interplay, occurs during emotional and physical arousal. It is well documented that physical and mental stress lead to sympathetic activation. Nevertheless, the role of autonomic inputs in nervous system-wise communication under mental stress is yet unknown. In this study, we estimated the causal and bidirectional neural modulations between electroencephalogram (EEG) oscillations and peripheral sympathetic and parasympathetic activities using a recently proposed computational framework for a functional brain-heart interplay assessment, namely the sympathovagal synthetic data generation model. Mental stress was elicited in 37 healthy volunteers by increasing their cognitive demands throughout three tasks associated with increased stress levels. Stress elicitation induced an increased variability in sympathovagal markers, as well as increased variability in the directional brain-heart interplay. The observed heart-to-brain interplay was primarily from sympathetic activity targeting a wide range of EEG oscillations, whereas variability in the efferent direction seemed mainly related to EEG oscillations in the γ band. These findings extend current knowledge on stress physiology, which mainly referred to top-down neural dynamics. Our results suggest that mental stress may not cause an increase in sympathetic activity exclusively as it initiates a dynamic fluctuation within brain-body networks including bidirectional interactions at a brain-heart level. We conclude that directional brain-heart interplay measurements may provide suitable biomarkers for a quantitative stress assessment and bodily feedback may modulate the perceived stress caused by increased cognitive demand. [ABSTRACT FROM AUTHOR] more...
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- 2023
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10. Closed‐loop modeling of central and intrinsic cardiac nervous system circuits underlying cardiovascular control.
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Gee, Michelle M., Lenhoff, Abraham M., Schwaber, James S., Ogunnaike, Babatunde A., and Vadigepalli, Rajanikanth
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NERVOUS system ,HEART ,LUNG volume ,EFFERENT pathways ,SINUS arrhythmia ,MOTOR neurons - Abstract
The baroreflex is a multi‐input, multi‐output physiological control system that regulates blood pressure by modulating nerve activity between the brainstem and the heart. Existing computational models of the baroreflex do not explicitly incorporate the intrinsic cardiac nervous system (ICN), which mediates central control of heart function. We developed a computational model of closed‐loop cardiovascular control by integrating a network representation of the ICN within central control reflex circuits. We examined central and local contributions to the control of heart rate, ventricular functions, and respiratory sinus arrhythmia (RSA). Our simulations match the experimentally observed relationship between RSA and lung tidal volume. Our simulations predicted the relative contributions of the sensory and the motor neuron pathways to the experimentally observed changes in the heart rate. Our closed‐loop cardiovascular control model is primed for evaluating bioelectronic interventions to treat heart failure and renormalize cardiovascular physiology. [ABSTRACT FROM AUTHOR] more...
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- 2023
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11. An optimal regulation of fluxes dictates microbial growth in and out of steady state
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Griffin Chure and Jonas Cremer
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resource allocation ,cell biology ,microbial physiology ,systems biology ,physiological modeling ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Effective coordination of cellular processes is critical to ensure the competitive growth of microbial organisms. Pivotal to this coordination is the appropriate partitioning of cellular resources between protein synthesis via translation and the metabolism needed to sustain it. Here, we extend a low-dimensional allocation model to describe the dynamic regulation of this resource partitioning. At the core of this regulation is the optimal coordination of metabolic and translational fluxes, mechanistically achieved via the perception of charged- and uncharged-tRNA turnover. An extensive comparison with ≈ 60 data sets from Escherichia coli establishes this regulatory mechanism’s biological veracity and demonstrates that a remarkably wide range of growth phenomena in and out of steady state can be predicted with quantitative accuracy. This predictive power, achieved with only a few biological parameters, cements the preeminent importance of optimal flux regulation across conditions and establishes low-dimensional allocation models as an ideal physiological framework to interrogate the dynamics of growth, competition, and adaptation in complex and ever-changing environments. more...
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- 2023
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12. Motor Control
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Catrambone, Vincenzo, Valenza, Gaetano, Catrambone, Vincenzo, and Valenza, Gaetano
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- 2021
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13. Sleep
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Catrambone, Vincenzo, Valenza, Gaetano, Catrambone, Vincenzo, and Valenza, Gaetano
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- 2021
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14. Psychiatric and Neurological Disorders
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Catrambone, Vincenzo, Valenza, Gaetano, Catrambone, Vincenzo, and Valenza, Gaetano
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- 2021
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15. Sympathovagal Changes
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Catrambone, Vincenzo, Valenza, Gaetano, Catrambone, Vincenzo, and Valenza, Gaetano
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- 2021
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16. BHI Estimation Methodology
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Catrambone, Vincenzo, Valenza, Gaetano, Catrambone, Vincenzo, and Valenza, Gaetano
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- 2021
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17. What Is QSP and Why Does It Exist?: A Brief History.
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Friedrich C
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Quantitative systems pharmacology (QSP) is a modeling approach employed in drug research and development that combines mechanistic representations of biological processes with drug pharmacology to deepen biological understanding and predict the responses to novel drugs or protocols. QSP has evolved from and is related to other modeling approaches, but has a number of unique attributes and applications. Here, we clarify the definition of QSP and its key features, trace its evolution, briefly compare it to other approaches, and explain why and how it can be used to reduce risk and improve efficiency in drug research and development., (© 2024. The Author(s), under exclusive license to Springer Nature Switzerland AG.) more...
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- 2024
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18. Development of a bioheat model for older people under hot and cold exposures.
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Ji, Lili, Laouadi, Abdelaziz, Wang, Liangzhu, and Lacasse, Michael A.
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Physiological modeling is important to evaluate the effects of heat and cold conditions on people's thermal comfort and health. Experimental studies have found that older people (above 65 year old) undergo age-related weakening changes in their physiology and thermoregulatory activities, which makes them more vulnerable to heat or cold exposure than average aged young adults. However, addressing the age-related changes by modeling has been challenging due to their wide variability among the older population. This study develops a two-node physiological model to predict the thermal response of older people. The model is built on a newly developed two-node model for average-age young adults by accounting for the age-related attenuation of thermoregulation and sensory delays in triggering thermoregulatory actions. A numerical optimization method is developed to compute the model parameter values based on selected benchmark data from the literature. The proposed model is further validated with published measurement data covering large input ranges. The model predictions are in good agreement with the measurements in hot and cold exposure conditions with a discrepancy 0.60 °C for the mean skin temperature and of 0.30 °C for the core temperature. The proposed model can be integrated into building simulation tools to predict heat and cold stress levels and the associated thermal comfort for older people in built environments. [ABSTRACT FROM AUTHOR] more...
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- 2022
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19. Modeling of Carbohydrates Oxidation Rate During Exercise in Type 1 Highly-Trained Diabetic Patients
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Francescato, Maria Pia, Ajčević, Miloš, Stella, Alex Buoite, Accardo, Agostino, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Henriques, Jorge, editor, Neves, Nuno, editor, and de Carvalho, Paulo, editor more...
- Published
- 2020
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20. CT Perfusion Techniques and Applications in Stroke and Cancer
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Lee, Ting-Yim, Yang, Dae Myoung, Li, Fiona, Marants, Raanan, Samei, Ehsan, editor, and Pelc, Norbert J., editor
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- 2020
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21. Quantitative estimation of nerve fiber engagement by vagus nerve stimulation using physiological markers
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Yao-Chuan Chang, Marina Cracchiolo, Umair Ahmed, Ibrahim Mughrabi, Arielle Gabalski, Anna Daytz, Loren Rieth, Lance Becker, Timir Datta-Chaudhuri, Yousef Al-Abed, Theodoros P. Zanos, and Stavros Zanos more...
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Vagus nerve stimulation ,Biomarker ,Bioelectronic medicine ,Compound nerve action potential ,Physiological modeling ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Background: Cervical vagus nerve stimulation (VNS) is an emerging bioelectronic treatment for brain, metabolic, cardiovascular and immune disorders. Its desired and off-target effects are mediated by different nerve fiber populations and knowledge of their engagement could guide calibration and monitoring of VNS therapies. Objective: Stimulus-evoked compound action potentials (eCAPs) directly provide fiber engagement information but are currently not feasible in humans. A method to estimate fiber engagement through common, noninvasive physiological readouts could be used in place of eCAP measurements. Methods: In anesthetized rats, we recorded eCAPs while registering acute physiological response markers to VNS: cervical electromyography (EMG), changes in heart rate (ΔHR) and breathing interval (ΔBI). Quantitative models were established to capture the relationship between A-, B- and C-fiber type activation and those markers, and to quantitatively estimate fiber activation from physiological markers and stimulation parameters. Results: In bivariate analyses, we found that EMG correlates with A-fiber, ΔHR with B-fiber and ΔBI with C-fiber activation, in agreement with known physiological functions of the vagus. We compiled multivariate models for quantitative estimation of fiber engagement from these markers and stimulation parameters. Finally, we compiled frequency gain models that allow estimation of fiber engagement at a wide range of VNS frequencies. Our models, after calibration in humans, could provide noninvasive estimation of fiber engagement in current and future therapeutic applications of VNS. more...
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- 2020
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22. Functional assessment of bidirectional cortical and peripheral neural control on heartbeat dynamics: A brain-heart study on thermal stress
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Diego Candia-Rivera, Vincenzo Catrambone, Riccardo Barbieri, and Gaetano Valenza
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Brain-heart interplay ,Physiological modeling ,Synthetic data generation ,Sympathovagal estimation ,Cold-pressor test ,Heart rate variability ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
The study of functional Brain-Heart Interplay (BHI) from non-invasive recordings has gained much interest in recent years. Previous endeavors aimed at understanding how the two dynamical systems exchange information, providing novel holistic biomarkers and important insights on essential cognitive aspects and neural system functioning. However, the interplay between cardiac sympathovagal and cortical oscillations still has much room for further investigation. In this study, we introduce a new computational framework for a functional BHI assessment, namely the Sympatho-Vagal Synthetic Data Generation Model, combining cortical (electroencephalography, EEG) and peripheral (cardiac sympathovagal) neural dynamics. The causal, bidirectional neural control on heartbeat dynamics was quantified on data gathered from 26 human volunteers undergoing a cold-pressor test. Results show that thermal stress induces heart-to-brain functional interplay sustained by EEG oscillations in the delta and gamma bands, primarily originating from sympathetic activity, whereas brain-to-heart interplay originates over central brain regions through sympathovagal control. The proposed methodology provides a viable computational tool for the functional assessment of the causal interplay between cortical and cardiac neural control. more...
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- 2022
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23. Analysis of Glucose Responsive Glucagon Therapeutics using Computational Models of the Glucoregulatory System.
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Alizadehmojarad AA, Yang S, Gong X, and Strano MS
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- Animals, Humans, Mice, Rats, Insulin metabolism, Computer Simulation, Glucose metabolism, Models, Biological, Hypoglycemia metabolism, Hypoglycemia drug therapy, Glucagon metabolism, Diabetes Mellitus, Type 1 drug therapy, Diabetes Mellitus, Type 1 metabolism, Blood Glucose metabolism
- Abstract
Glucose-responsive glucagon (GRG) therapeutics are a promising technology for reducing the risk of severe hypoglycemia as a complication of diabetes mellitus. Herein, the performance of candidate GRGs in the literature by modeling the kinetics of activation and connecting them as input into physiological glucoregulatory models is evaluated and projected the two distinct GRG designs, experimental results reported in Wu et al. (GRG-I) and Webber et al. (GRG-II) is considered. Both are evaluated using a multi-compartmental glucoregulatory model (IMPACT) and used to compare in-vivo experimental data of therapeutic performance in rats and mice. For GRG-I and GRG-II, the total integrated glucose material balances are overestimated by 41.5% ± 14% and underestimated by 24.8% ± 16% compared to in-vivo time-course data, respectively. These large differences to the relatively simple computational descriptions of glucagon dynamics in the model, which underscores the urgent need for improved glucagon models is attributed. Additionally, therapeutic insulin and glucagon infusion pumps are modeled for type 1 diabetes mellitus (T1DM) human subjects to extend the results to additional datasets. These observations suggest that both the representative physiological and non-physiological models considered in this work require additional refinement to successfully describe clinical data that involve simultaneous, coupled insulin, glucose, and glucagon dynamics., (© 2024 The Author(s). Advanced Healthcare Materials published by Wiley‐VCH GmbH.) more...
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- 2024
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24. Brain-heart interactions in the neurobiology of consciousness
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Diego Candia-Rivera
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Physiological modeling ,Brain-heart interplay ,Heartbeat-evoked responses ,Heart rate variability ,Interoception ,Consciousness ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Recent experimental evidence on patients with disorders of consciousness revealed that observing brain-heart interactions helps to detect residual consciousness, even in patients with absence of behavioral signs of consciousness. Those findings support hypotheses suggesting that visceral activity is involved in the neurobiology of consciousness, and sum to the existing evidence in healthy participants in which the neural responses to heartbeats reveal perceptual and self-consciousness. More evidence obtained through mathematical modeling of physiological dynamics revealed that emotion processing is prompted by an initial modulation from ascending vagal inputs to the brain, followed by sustained bidirectional brain-heart interactions. Those findings support long-lasting hypotheses on the causal role of bodily activity in emotions, feelings, and potentially consciousness. In this paper, the theoretical landscape on the potential role of heartbeats in cognition and consciousness is reviewed, as well as the experimental evidence supporting these hypotheses. I advocate for methodological developments on the estimation of brain-heart interactions to uncover the role of cardiac inputs in the origin, levels, and contents of consciousness. The ongoing evidence depicts interactions further than the cortical responses evoked by each heartbeat, suggesting the potential presence of non-linear, complex, and bidirectional communication between brain and heartbeat dynamics. Further developments on methodologies to analyze brain-heart interactions may contribute to a better understanding of the physiological dynamics involved in homeostatic-allostatic control, cognitive functions, and consciousness. more...
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- 2022
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25. Review of applications and challenges of quantitative systems pharmacology modeling and machine learning for heart failure.
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Cheng, Limei, Qiu, Yuchi, Schmidt, Brian J., and Wei, Guo-Wei
- Abstract
Quantitative systems pharmacology (QSP) is an important approach in pharmaceutical research and development that facilitates in silico generation of quantitative mechanistic hypotheses and enables in silico trials. As demonstrated by applications from numerous industry groups and interest from regulatory authorities, QSP is becoming an increasingly critical component in clinical drug development. With rapidly evolving computational tools and methods, QSP modeling has achieved important progress in pharmaceutical research and development, including for heart failure (HF). However, various challenges exist in the QSP modeling and clinical characterization of HF. Machine/deep learning (ML/DL) methods have had success in a wide variety of fields and disciplines. They provide data-driven approaches in HF diagnosis and modeling, and offer a novel strategy to inform QSP model development and calibration. The combination of ML/DL and QSP modeling becomes an emergent direction in the understanding of HF and clinical development new therapies. In this work, we review the current status and achievement in QSP and ML/DL for HF, and discuss remaining challenges and future perspectives in the field. [ABSTRACT FROM AUTHOR] more...
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- 2022
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26. Blood Glucose Regulation Models in Artificial Pancreas for Type-1 Diabetic Patients
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Chandrasekhar, Abishek and Padhi, Radhakant
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- 2023
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27. Wearable Sensor Technology to Predict Core Body Temperature: A Systematic Review
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Conor M. Dolson, Ethan R. Harlow, Dermot M. Phelan, Tim J. Gabbett, Benjamin Gaal, Christopher McMellen, Benjamin J. Geletka, Jacob G. Calcei, James E. Voos, and Dhruv R. Seshadri
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wearable technology ,core body temperature ,heat stroke ,exertional heat illness ,physiological modeling ,machine learning ,Chemical technology ,TP1-1185 - Abstract
Heat-related illnesses, which range from heat exhaustion to heatstroke, affect thousands of individuals worldwide every year and are characterized by extreme hyperthermia with the core body temperature (CBT) usually > 40 °C, decline in physical and athletic performance, CNS dysfunction, and, eventually, multiorgan failure. The measurement of CBT has been shown to predict heat-related illness and its severity, but the current measurement methods are not practical for use in high acuity and high motion settings due to their invasive and obstructive nature or excessive costs. Noninvasive predictions of CBT using wearable technology and predictive algorithms offer the potential for continuous CBT monitoring and early intervention to prevent HRI in athletic, military, and intense work environments. Thus far, there has been a lack of peer-reviewed literature assessing the efficacy of wearable devices and predictive analytics to predict CBT to mitigate heat-related illness. This systematic review identified 20 studies representing a total of 25 distinct algorithms to predict the core body temperature using wearable technology. While a high accuracy in prediction was noted, with 17 out of 18 algorithms meeting the clinical validity standards. few algorithms incorporated individual and environmental data into their core body temperature prediction algorithms, despite the known impact of individual health and situational and environmental factors on CBT. Robust machine learning methods offer the ability to develop more accurate, reliable, and personalized CBT prediction algorithms using wearable devices by including additional data on user characteristics, workout intensity, and the surrounding environment. The integration and interoperability of CBT prediction algorithms with existing heat-related illness prevention and treatment tools, including heat indices such as the WBGT, athlete management systems, and electronic medical records, will further prevent HRI and increase the availability and speed of data access during critical heat events, improving the clinical decision-making process for athletic trainers and physicians, sports scientists, employers, and military officers. more...
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- 2022
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28. Modeling of glycogen resynthesis according to insulin concentration: towards a system for prevention of late-onset exercise-induced hypoglycemia in Type 1 diabetes patients.
- Author
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Ajčević, Miloš, Accardo, Agostino, and Pia Francescato, Maria
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TYPE 1 diabetes ,HYPOGLYCEMIA ,ARTIFICIAL pancreases ,GLYCOGEN ,PEOPLE with diabetes ,INSULIN ,INSULIN pumps ,ISOMETRIC exercise - Abstract
One of the major barriers for physical activity in type 1 diabetes (T1D) patients is the risk of exercise-induced hypoglycemia, in particular the late-onset one. The identification of the relation between glycogen resynthesis rate after an exercise and insulin concentration would allow the development of new predictive models. The aim of the present work was thus to investigate this relation in T1D patients. We recruited 8 T1D subjects which underwent two 24-h observational experimental sessions: complete rest and a 3-hours treadmill walk. Glucose and insulin concentrations were measured throughout the two sessions. Comparing the data collected in the two sessions, the net glucose uptake was calculated; positive values were suggestive of glycogen repletion while negative values suggested liver glycogen breakdown. A significant correlation (r=0.742, p<0.001) was observed between insulin concentration and net glucose uptake, with the negative values corresponding to time periods showing the lowest insulin concentrations. In conclusion, the present study preliminarily assessed the impact of insulin concentration on the risk of late onset hypoglycemia, which is the first step towards a comprehensive and personalized system for prevention of exercise-induced hypoglycemia in Type 1 diabetes patients. [ABSTRACT FROM AUTHOR] more...
- Published
- 2021
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29. Flow-mediated dilation analysis coupled with nitric oxide transport to enhance the assessment of endothelial function.
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Tianxiang Ma, Xiao Liu, Quan Ren, Zhexi Zhang, Xiaoning Sun, Yuehong Zheng, Xiaoyan Deng, Xiaojun Yu, and Yubo Fan
- Abstract
Flow-mediated dilation (FMD), mainly mediated by nitric oxide (NO), aims to assess the shear-induced endothelial function, which is widely quantified by the relative change in arterial diameter after dilation (FMD%). However, FMD% is affected by individual differences in blood pressure, blood flow, and arterial diameter. To reduce these differences and enhance the assessment of FMD to endothelial function, we continuously measured not only the brachial artery diameter and blood flow with ultrasound but also blood pressure with noninvasive monitor during standard FMD test. We further constructed an analytical model of FMD coupled with NO transport, blood flow, and arterial deformation. Combining the time-averaged and peak values of arterial diameter, blood flow, and pressure, and the modeling, we assumed the artery was completely healthy and calculated an ideally expected FMD% (eFMD%). Then, we expressed the fractional flow-mediated dilation (FFMD%) for the ratio of measured FMD% (mFMD%) to eFMD%. Furthermore, using the continuous waveforms of arterial diameter, blood flow, and pressure, the endothelial characteristic parameter (𝝐) was calculated, which describes the function of the endothelium to produce NO and ranges from 1 to 0 representing the endothelial function from healthiness to complete loss. We found that the mFMD% and eFMD% between the young age (n = 5, 21.2 ± 1.8 yr) and middle age group (n = 5, 34.0 ± 2.1 yr) have no significant difference (P = 0.222, P = 0.385). In contrast, the FFMD% (P = 0.008) and 𝝐 (P = 0.007) both show significant differences. Therefore, the fractional flow-mediated dilation (FFMD%) and the endothelial characteristic parameter (𝝐) may have the potential for specifically diagnosing the endothelial function. [ABSTRACT FROM AUTHOR] more...
- Published
- 2021
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30. Computational modeling for the quantitative assessment of cardiac autonomic response to orthostatic stress.
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Wang T, Wu J, Qin F, Jiang H, Xiao X, and Huang Z
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- Humans, Male, Heart physiology, Dizziness physiopathology, Adult, Female, Computer Simulation, Autonomic Nervous System physiopathology, Autonomic Nervous System physiology, Heart Rate physiology
- Abstract
Objective. The autonomic nervous system (ANS) plays a critical role in regulating not only cardiac functions but also various other physiological processes, such as respiratory rate, digestion, and metabolic activities. The ANS is divided into the sympathetic and parasympathetic nervous systems, each of which has distinct but complementary roles in maintaining homeostasis across multiple organ systems in response to internal and external stimuli. Early detection of ANS dysfunctions, such as imbalances between the sympathetic and parasympathetic branches or impairments in the autonomic regulation of bodily functions, is crucial for preventing or slowing the progression of cardiovascular diseases. These dysfunctions can manifest as irregularities in heart rate, blood pressure regulation, and other autonomic responses essential for maintaining cardiovascular health. Traditional methods for analyzing ANS activity, such as heart rate variability (HRV) analysis and muscle sympathetic nerve activity recording, have been in use for several decades. Despite their long history, these techniques face challenges such as poor temporal resolution, invasiveness, and insufficient sensitivity to individual physiological variations, which limit their effectiveness in personalized health assessments. Approach. This study aims to introduce the open-loop Mathematical Model of Autonomic Regulation of the Cardiac System under Supine-to-stand Maneuver (MMARCS) to overcome the limitations of existing ANS analysis methods. The MMARCS model is designed to offer a balance between physiological fidelity and simplicity, focusing on the ANS cardiac control subsystems' input-output curve. The MMARCS model simplifies the complex internal dynamics of ANS cardiac control by emphasizing input-output relationships and utilizing sensitivity analysis and parameter subset selection to increase model specificity and eliminate redundant parameters. This approach aims to enhance the model's capacity for personalized health assessments. Main results. The application of the MMARCS model revealed significant differences in ANS regulation between healthy (14 females and 19 males, age: 42 ± 18) and diabetic subjects (8 females and 6 males, age: 47 ± 14). Parameters indicated heightened sympathetic activity and diminished parasympathetic response in diabetic subjects compared to healthy subjects ( p < 0.05). Additionally, the data suggested a more sensitive and potentially more reactive sympathetic response among diabetic subjects ( p < 0.05), characterized by increased responsiveness and intensity of the sympathetic nervous system to stimuli, i.e. fluctuations in blood pressure, leading to more pronounced changes in heart rate, these phenomena can be directly reflected by gain parameters and time response parameters of the model. Significance. The MMARCS model represents an innovative computational approach for quantifying ANS functionality. This model guarantees the accuracy of physiological modeling while reducing mathematical complexity, offering an easy-to-implement and widely applicable tool for clinical measurements of cardiovascular health, disease progression monitoring, and home health monitoring through wearable technology., (© 2024 Institute of Physics and Engineering in Medicine.) more...
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- 2024
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31. Quantitative estimation of nerve fiber engagement by vagus nerve stimulation using physiological markers.
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Chang, Yao-Chuan, Cracchiolo, Marina, Ahmed, Umair, Mughrabi, Ibrahim, Gabalski, Arielle, Daytz, Anna, Rieth, Loren, Becker, Lance, Datta-Chaudhuri, Timir, Al-Abed, Yousef, Zanos, Theodoros P., and Zanos, Stavros more...
- Abstract
Cervical vagus nerve stimulation (VNS) is an emerging bioelectronic treatment for brain, metabolic, cardiovascular and immune disorders. Its desired and off-target effects are mediated by different nerve fiber populations and knowledge of their engagement could guide calibration and monitoring of VNS therapies. Stimulus-evoked compound action potentials (eCAPs) directly provide fiber engagement information but are currently not feasible in humans. A method to estimate fiber engagement through common, noninvasive physiological readouts could be used in place of eCAP measurements. In anesthetized rats, we recorded eCAPs while registering acute physiological response markers to VNS: cervical electromyography (EMG), changes in heart rate (ΔHR) and breathing interval (ΔBI). Quantitative models were established to capture the relationship between A-, B- and C-fiber type activation and those markers, and to quantitatively estimate fiber activation from physiological markers and stimulation parameters. In bivariate analyses, we found that EMG correlates with A-fiber, ΔHR with B-fiber and ΔBI with C-fiber activation, in agreement with known physiological functions of the vagus. We compiled multivariate models for quantitative estimation of fiber engagement from these markers and stimulation parameters. Finally, we compiled frequency gain models that allow estimation of fiber engagement at a wide range of VNS frequencies. Our models, after calibration in humans, could provide noninvasive estimation of fiber engagement in current and future therapeutic applications of VNS. • Robust correlations are documented between engagement of different fiber types by VNS and noninvasive physiological markers. • A-type fibers with laryngeal EMG, B fibers with changes in heart rate, C fibers with changes in breathing interval. • Fiber engagement is quantitatively estimated by quadratic models using those physiological markers and stimulation parameters. • Frequency gain models expand the application of those models to a wide range of VNS pulsing frequencies. • Such models, after calibration in humans, could provide noninvasive estimation of fiber engagement to guide VNS therapy calibration and monitoring. [ABSTRACT FROM AUTHOR] more...
- Published
- 2020
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32. A Modular Patient Simulator for Evaluation of Decision Support Algorithms in Mechanically Ventilated Patients
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Kretschmer, Jörn, Lehmann, Thomas, Redmond, Daniel, Stehle, Patrick, Möller, Knut, Magjarevic, Ratko, Editor-in-chief, Ładyżyński, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, Kyriacou, Efthyvoulos, editor, Christofides, Stelios, editor, and Pattichis, Constantinos S., editor more...
- Published
- 2016
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33. Cardiovascular to Intracranial Transmission Characteristics for Hydrocephalus
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Misgeld, Berno J. E., Mondal, Rajib, Leonhardt, Steffen, Rubin, Wang, Series editor, Wang, Rubin, editor, and Pan, Xiaochuan, editor
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- 2016
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34. Modeling and Analysis of the Intrinsic Cardiac Nervous System in Closed-Loop Cardiovascular Control
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Gee, Michelle M., Lenhoff, Abraham M., Schwaber, James S., Ogunnaike, Babatunde A., Vadigepalli, Rajanikanth, Gee, Michelle M., Lenhoff, Abraham M., Schwaber, James S., Ogunnaike, Babatunde A., and Vadigepalli, Rajanikanth more...
- Abstract
The baroreceptor reflex is a multi-input, multi-output physiological control system that regulates short-term blood pressure by modulating nerve activity between the brainstem and the heart. The computational model by Park et al. (2020) is the most recent iteration in our exploration of the system. However, the contributions of”the little brain of the heart”, the intrinsic cardiac nervous system (ICN), to local control of the heart and to the integration of sensory information is unknown and has been overlooked in previous models. We have incorporated a high-fidelity representation of the ICN into a model of the baroreceptor reflex based on anatomical, molecular, and physiological evidence. The model consists of (1) differential equations to represent the cardiovascular system, and (2) transfer functions to represent neural control components, connected in a closed-loop control circuit. We use the model to evaluate the impact of alternative ICN network structures on overall cardiovascular control in response to mean arterial pressure and lung tidal volume perturbations. Our results show that the local circuit neurons that integrate sensory information into the ICN strengthen the response of ICN neuron activity, especially at low blood pressures, suggesting that the ICN amplifies the brainstem's response to perturbations. more...
- Published
- 2023
35. Modeling and Control of Physiological Systems
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Kovacs, L., MAGJAREVIC, Ratko, Editor-in-chief, Ładyzynsk, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, and Jobbágy, Ákos, editor more...
- Published
- 2015
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36. Preeminent role of the cardiorenal axis in the antihypertensive response to an arteriovenous fistula: an in silico analysis.
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Clemmer, John S., Pruett, W. Andrew, Hester, Robert L., and Lohmeier, Thomas E.
- Subjects
- *
ARTERIOVENOUS fistula , *BLOOD pressure , *CARDIAC output , *HUMAN physiology , *MECHANORECEPTORS - Abstract
Percutaneous creation of a small central arteriovenous (AV) fistula is currently being evaluated for the treatment of uncontrolled hypertension (HT). Although the mechanisms that contribute to the antihypertensive effects of the fistula are unclear, investigators have speculated that chronic blood pressure (BP) lowering may be due to 1) reduced total peripheral resistance (TPR), 2) increased secretion of atrial natriuretic peptide (ANP), and/or 3) suppression of renal sympathetic nerve activity (RSNA). We used an established integrative mathematical model of human physiology to investigate these possibilities from baseline conditions that mimic sympathetic overactivity and impaired renal function in patients with resistant HT. After a small fistula was stimulated, there were sustained increases in cardiac output, atrial pressures, and plasma ANP concentration (3-fold), without suppression of RSNA; at 8 wk, BP was reduced 14 mmHg along with a 32% fall in TPR. In contrast, when this simulation was repeated while clamping ANP at baseline BP decreased only 4 mmHg, despite a comparable fall in TPR. Furthermore, when chronic resetting of atrial mechanoreceptors was prevented during the fistula, RSNA decreased 7%, and along with the same threefold increase in ANP, BP fell 19 mmHg. This exaggerated fall in BP occurred with a similar decrease in TPR when compared with the above simulations. These findings suggest that ANP, but not TPR, is a key determinant of long-term BP lowering after the creation of an AV fistula and support a contribution of suppressed RSNA if resetting of the atrial-renal reflex is truly incomplete. [ABSTRACT FROM AUTHOR] more...
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- 2019
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37. A methodology of phenotyping ICU patients from EHR data: High-fidelity, personalized, and interpretable phenotypes estimation.
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Wang, Yanran, Stroh, J.N., Hripcsak, George, Low Wang, Cecilia C., Bennett, Tellen D., Wrobel, Julia, Der Nigoghossian, Caroline, Mueller, Scott W., Claassen, Jan, and Albers, D.J.
- Abstract
Computing phenotypes that provide high-fidelity, time-dependent characterizations and yield personalized interpretations is challenging, especially given the complexity of physiological and healthcare systems and clinical data quality. This paper develops a methodological pipeline to estimate unmeasured physiological parameters and produce high-fidelity, personalized phenotypes anchored to physiological mechanics from electronic health record (EHR). A methodological phenotyping pipeline is developed that computes new phenotypes defined with unmeasurable computational biomarkers quantifying specific physiological properties in real time. Working within the inverse problem framework, this pipeline is applied to the glucose-insulin system for ICU patients using data assimilation to estimate an established mathematical physiological model with stochastic optimization. This produces physiological model parameter vectors of clinically unmeasured endocrine properties, here insulin secretion, clearance, and resistance, estimated for individual patient. These physiological parameter vectors are used as inputs to unsupervised machine learning methods to produce phenotypic labels and discrete physiological phenotypes. These phenotypes are inherently interpretable because they are based on parametric physiological descriptors. To establish potential clinical utility, the computed phenotypes are evaluated with external EHR data for consistency and reliability and with clinician face validation. The phenotype computation was performed on a cohort of 109 ICU patients who received no or short-acting insulin therapy, rendering continuous and discrete physiological phenotypes as specific computational biomarkers of unmeasured insulin secretion, clearance, and resistance on time windows of three days. Six, six, and five discrete phenotypes were found in the first, middle, and last three-day periods of ICU stays, respectively. Computed phenotypic labels were predictive with an average accuracy of 89%. External validation of discrete phenotypes showed coherence and consistency in clinically observable differences based on laboratory measurements and ICD 9/10 codes and clinical concordance from face validity. A particularly clinically impactful parameter, insulin secretion, had a concordance accuracy of 83% ± 27%. The new physiological phenotypes computed with individual patient ICU data and defined by estimates of mechanistic model parameters have high physiological fidelity, are continuous, time-specific, personalized, interpretable, and predictive. This methodology is generalizable to other clinical and physiological settings and opens the door for discovering deeper physiological information to personalize medical care. [Display omitted] • A methodological phenotyping pipeline is developed. • The pipeline extracts unmeasurable computational biomarkers from sparse EHR data. • The pipeline computes new physiological phenotypes with individual patient ICU data. • Computed phenotypes are high-fidelity, interpretable, and time-specific. • The methodology is generalizable to other clinical and physiological settings. [ABSTRACT FROM AUTHOR] more...
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- 2023
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38. A New Oral Model to Assess Postprandial Lactate Production Rate
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Jacopo Bonet, Nicola Santoro, Brittany Galuppo, and Chiara Dalla-Man
- Subjects
Blood Glucose ,obesity ,medicine.medical_specialty ,Adolescent ,medicine.medical_treatment ,Biomedical Engineering ,prediabetes ,diabetes ,identifiability ,parameter estimation ,Physiological modeling ,Article ,chemistry.chemical_compound ,Insulin resistance ,Internal medicine ,Diabetes mellitus ,Medicine ,Humans ,Insulin ,Glycolysis ,Prediabetes ,Lactic Acid ,Child ,business.industry ,Fatty liver ,Acetyl-CoA ,Glucose Tolerance Test ,medicine.disease ,Postprandial Period ,Endocrinology ,Postprandial ,Glucose ,chemistry ,Insulin Resistance ,business - Abstract
Objective: Pediatric obesity predisposes children and adolescents to early onset insulin resistance and dysglycemia. In the last 20 years this has led to a rise in the prevalence of prediabetes, diabetes and fatty liver in youngsters, due to the high degree of insulin resistance experienced by these patients and the consequent high availability of glucose. As glucose accesses the liver, it is partly metabolized through glycolysis, whose main product is pyruvate that is then converted into Acetyl CoA and lactate. Therefore, lactate production rate (LPR) represents the best proxy for the assessment of glycolysis. Since to date there are not methods to estimate postprandial LPR, here we proposed a novel oral glucose-lactate model to estimate LPR during an oral glucose tolerance test and tested it in 24 youth with and without obesity. Methods: The model is based on the oral glucose minimal model and assumes that LPR is a fraction (fr) of glucose disposal rate, proportional to glucose concentration and controlled by insulin action. Results: The model well fitted the glucose and lactate data, and provided both precise parameter estimates (e.g. fr=22.5 [12.6-54.1]%, median [IQR]), CV=18 [13-25]%) and LPR time course. Conclusions: The proposed model is a valid tool to assess LPR, and thus glycolysis, during OGTT in nondiabetic subjects. Significance: The proposed methodology will allow to assess postprandial LPR in simple and cost-effective way. more...
- Published
- 2023
39. Integration of Smart Home Health Data in the Clinical Decision Making Process
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Helmer, Axel, Müller, Frerk, Lohmann, Okko, Thiel, Andreas, Kretschmer, Friedrich, Eichelberg, Marco, Hein, Andreas, Fernández-Chimeno, Mireya, editor, Fernandes, Pedro L., editor, Alvarez, Sergio, editor, Stacey, Deborah, editor, Solé-Casals, Jordi, editor, Fred, Ana, editor, and Gamboa, Hugo, editor more...
- Published
- 2014
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40. A Hierarchical Model Family of Human Gas Exchange for the Use in Medical Decision Support
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Kretschmer, J., Riedlinger, A., Möller, K., MAGJAREVIC, Ratko, Editor-in-chief, Ładyzynsk, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lackovic, Igor, Series editor, Rock, Emilio Sacristan, Series editor, and Goh, James, editor more...
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- 2014
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41. Coronary Smooth Muscle Cell Calcium Dynamics: Effects of Bifurcation Angle on Atheroprone Conditions
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Stewart Dowding, Constantine Zakkaroff, Stephen Moore, and Tim David
- Subjects
coupled arterial cells ,endothelial cells ,smooth muscle cells ,atherosclerosis ,physiological modeling ,parallel simulations ,Physiology ,QP1-981 - Abstract
This work investigates the effect of arterial bifurcation angulation on atherosclerosis development through in-silico simulations of coupled cell dynamics. The computational model presented here combines cellular pathways, fluid dynamics, and physiologically-realistic vessel geometries as observed in the human vasculature. The coupled cells model includes endothelial cells (ECs) and smooth muscle cells (SMCs) with ion dynamics, hetero and homotypic coupling, as well as electro-diffusive coupling. Three arterial bifurcation surface models were used in the coupled cells simulations. All three simulations showed propagating waves of Ca2+ in both the SMC and EC layers, following the introduction of a luminal agonist, in this case ATP. Immediately following the introduction of ATP concentration Ca2+ waves propagate from the area of high ATP toward the areas of low ATP concentration, forming complex patterns where waves interact with eachother, collide and fade. These dynamic phenomena are repeated with a series of waves of slower velocity. The underlying motivation of this research was to examine the macro-scale phenomena, given that the characteristic length scales of atherosclerotic plaques are much larger than a single cell. The micro-scale dynamics were modeled on macro-scale arterial bifurcation surfaces containing over one million cells. The results of the simulations presented here suggest that susceptibility to atherosclerosis development depends on the bifurcation angulation. In conjunction with findings reported in the literature, the simulation results demonstrate that arterial bifurcations containing wider angles have a more prominent influence on the coupled cells pathways associated with the development of atherosclerosis, by means of disturbed flow and lower SMC Ca2+ concentrations. The discussion of the results considers the findings of this research within the context of the potential link between information transport through frequency encoding of Ca2+ wave dynamics and development of atheroprone conditions. more...
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- 2018
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42. A Time-Continuous Model of Respiratory Mechanics of ARDS Patients
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Schranz, C., Docherty, P. D., Chiew, Y. S., Chase, J. G., Möller, K., and Long, Mian, editor
- Published
- 2013
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43. Iterative computing of decoupled interacting models
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Kretschmer, J., Knöbel, C., Wingender, J., Möller, K., and Long, Mian, editor
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- 2013
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44. A physiological model of phrenic nerve excitation by electrical stimulation.
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Lohse A, Deininger MM, Loeser J, Roehren F, Ziles D, Breuer T, Leonhardt S, and Walter M
- Subjects
- Humans, Animals, Swine, Respiration, Artificial, Electric Stimulation, Atrophy, Diaphragm, Phrenic Nerve physiology
- Abstract
Mechanical ventilation is essential in intensive care treatment but leads to diaphragmatic atrophy, which in turn contributes to prolonged weaning and increased mortality. One approach to prevent diaphragmatic atrophy while achieving pulmonary ventilation is electrical stimulation of the phrenic nerve. To automize phrenic nerve stimulation resulting in lung protective tidal volumes with lowest possible currents, mathematical models are required. Nerve stimulation models are often complex, so many parameters have to be identified prior to implementation. This paper presents a novel, simplified approach to model phrenic nerve excitation to obtain an individualized patient model using a few data points. The latter is based on the idea that nerve fibers are excited when the electric field exceeds a threshold. The effect of the geometry parameter on the model output was analyzed, and the model was validated with measurement data from a pig trial (RMSE in between 0.44 × 10
-2 and 1.64 × 10-2 for parameterized models). The modeled phrenic nerve excitation behaved similarly to the measured tidal volumes, and thus could be used to develop automated phrenic nerve stimulation systems for lung protective ventilation., (© 2024 IOP Publishing Ltd.) more...- Published
- 2024
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45. Analysis of the Effects of Nitric Oxide on Vasomotion
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Abatay, H., Payne, S. J., Magjarevic, Ratko, editor, Lim, C. T., editor, and Goh, J. C. H., editor
- Published
- 2010
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46. Non-linear modeling of cerebral autoregulation using cascade models
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Angarita-Jaimes, N. C., Dewhirst, O. P., Simpson, D. M., Magjarevic, Ratko, editor, Bamidis, Panagiotis D., editor, and Pallikarakis, Nicolas, editor
- Published
- 2010
- Full Text
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47. Coronary Smooth Muscle Cell Calcium Dynamics: Effects of Bifurcation Angle on Atheroprone Conditions.
- Author
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Dowding, Stewart, Zakkaroff, Constantine, Moore, Stephen, and David, Tim
- Published
- 2018
- Full Text
- View/download PDF
48. Temporal dissociation between muscle and pulmonary oxygen uptake kinetics: influences of perfusion dynamics and arteriovenous oxygen concentration differences in muscles and lungs.
- Author
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Drescher, U., Koschate, J., Thieschäfer, L., Schneider, S., and Hoffmann, U.
- Subjects
- *
AEROBIC exercises , *AEROBIC capacity , *PERFUSION , *EXERCISE , *RESPIRATION , *CARDIOPULMONARY fitness - Abstract
Purpose: The aim of the study was to test whether or not the arteriovenous oxygen concentration difference (avDO2) kinetics at the pulmonary (avDO2pulm) and muscle (avDO2musc) levels is significantly different during dynamic exercise.Methods: A re-analysis involving six publications dealing with kinetic analysis was utilized with an overall sample size of 69 participants. All studies comprised an identical pseudorandom binary sequence work rate (WR) protocol-WR changes between 30 and 80 W-to analyze the kinetic responses of pulmonary ([Formula: see text]) and muscle ([Formula: see text]) oxygen uptake kinetics as well as those of avDO2pulm and avDO2musc.Results: A significant difference between [Formula: see text] (0.395 ± 0.079) and [Formula: see text] kinetics (0.330 ± 0.078) was observed (p < 0.001), where the variables showed a significant relationship (rSP = 0.744, p < 0.001). There were no significant differences between avDO2musc (0.446 ± 0.077) and avDO2pulm kinetics (0.451 ± 0.075), which are highly correlated (r = 0.929, p < 0.001).Conclusion: It is suggested that neither avDO2pulm nor avDO2musc kinetic responses seem to be responsible for the differences between estimated [Formula: see text] and measured [Formula: see text] kinetics. Obviously, the conflation of avDO2 and perfusion ([Formula: see text] ) at different points in time and at different physiological levels drive potential differences in [Formula: see text] and [Formula: see text] kinetics. Therefore, [Formula: see text] should, in general, be considered whenever oxygen uptake kinetics are analyzed or discussed. [ABSTRACT FROM AUTHOR] more...- Published
- 2018
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49. An object-oriented computational model to study cardiopulmonary hemodynamic interactions in humans.
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Ngo, Chuong, Dahlmanns, Stephan, Vollmer, Thomas, Misgeld, Berno, and Leonhardt, Steffen
- Subjects
- *
CARDIOPULMONARY system , *HEMODYNAMICS , *ALVEOLITIS , *ARTIFICIAL respiration - Abstract
Background and objective: This work introduces an object-oriented computational model to study cardiopulmonary interactions in humans. Methods: Modeling was performed in object-oriented programing language Matlab Simscape, where model components are connected with each other through physical connections. Constitutive and phenomenological equations of model elements are implemented based on their non-linear pressure–volume or pressure-flow relationship. The model includes more than 30 physiological compartments, which belong either to the cardiovascular or respiratory system. The model considers non-linear behaviors of veins, pulmonary capillaries, collapsible airways, alveoli, and the chest wall. Model parameters were derisved based on literature values. Model validation was performed by comparing simulation results with clinical and animal data reported in literature. Results: The model is able to provide quantitative values of alveolar, pleural, interstitial, aortic and ventricular pressures, as well as heart and lung volumes during spontaneous breathing and mechanical ventilation. Results of baseline simulation demonstrate the consistency of the assigned parameters. Simulation results during mechanical ventilation with PEEP trials can be directly compared with animal and clinical data given in literature. Conclusions: Object-oriented programming languages can be used to model interconnected systems including model non-linearities. The model provides a useful tool to investigate cardiopulmonary activity during spontaneous breathing and mechanical ventilation. [ABSTRACT FROM AUTHOR] more...
- Published
- 2018
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50. Parameter estimation of recruitment models in mechanical ventilation
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Möller, Knut, Sivenova, T., Runck, H., Stahl, C., Schumann, S., Guttmann, J., Magjarevic, R., editor, Nagel, J. H., editor, Vander Sloten, Jos, editor, Verdonck, Pascal, editor, Nyssen, Marc, editor, and Haueisen, Jens, editor more...
- Published
- 2009
- Full Text
- View/download PDF
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