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1. Unpacking the multimodal, multi‐scale data of the fast and slow lanes of the cardiac vagus through computational modelling

   https://doi.org/10.1113/EP090865  

   Gee, Michelle M. ; Hornung, Eden ; Gupta, Suranjana ; Newton, Adam J. H. ; Cheng, Zixi ; Lytton, William W. ; Lenhoff, Abraham M. ; Schwaber, James S. ; Vadigepalli, Rajanikanth ( April 2023 , Experimental Physiology)

   What is the topic of this review?

   The vagus nerve is a crucial regulator of cardiovascular homeostasis, and its activity is linked to heart health. Vagal activity originates from two brainstem nuclei: the nucleus ambiguus (fast lane) and the dorsal motor nucleus of the vagus (slow lane), nicknamed for the time scales that they require to transmit signals.

   What advances does it highlight?

   Computational models are powerful tools for organizing multi‐scale, multimodal data on the fast and slow lanes in a physiologically meaningful way. A strategy is laid out for how these models can guide experiments aimed at harnessing the cardiovascular health benefits of differential activation of the fast and slow lanes.

   The vagus nerve is a key mediator of brain–heart signaling, and its activity is necessary for cardiovascular health. Vagal outflow stems from the nucleus ambiguus, responsible primarily for fast, beat‐to‐beat regulation of heart rate and rhythm, and the dorsal motor nucleus of the vagus, responsible primarily for slow regulation of ventricular contractility. Due to the high‐dimensional and multimodal nature of the anatomical, molecular and physiological data on neural regulation of cardiac function, data‐derived mechanistic insights have proven elusive. Elucidating insights has been complicated further by the broad distribution of the data across heart, brain and peripheral nervous system circuits. Here we lay out an integrative framework based on computational modelling for combining these disparate and multi‐scale data on the two vagal control lanes of the cardiovascular system. Newly available molecular‐scale data, particularly single‐cell transcriptomic analyses, have augmented our understanding of the heterogeneous neuronal states underlying vagally mediated fast and slow regulation of cardiac physiology. Cellular‐scale computational models built from these data sets represent building blocks that can be combined using anatomical and neural circuit connectivity, neuronal electrophysiology, and organ/organismal‐scale physiology data to create multi‐system, multi‐scale models that enablein silicoexploration of the fast versus slow lane vagal stimulation. The insights from the computational modelling and analyses will guide new experimental questions on the mechanisms regulating the fast and slow lanes of the cardiac vagus toward exploiting targeted vagal neuromodulatory activity to promote cardiovascular health.

    

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2. An algorithm for coupling multibranch in vitro experiment to numerical physiology simulation for a hybrid cardiovascular model

   https://doi.org/10.1002/cnm.3289  

   Mirzaei, Ehsan ; Farahmand, Masoud ; Kung, Ethan ( December 2019 , International Journal for Numerical Methods in Biomedical Engineering)

   The hybrid cardiovascular modeling approach integrates an in vitro experiment with a computational lumped‐parameter simulation, enabling direct physical testing of medical devices in the context of closed‐loop physiology. The interface between the in vitro and computational domains is essential for properly capturing the dynamic interactions of the two. To this end, we developed an iterative algorithm capable of coupling an in vitro experiment containing multiple branches to a lumped‐parameter physiology simulation. This algorithm identifies the unique flow waveform solution for each branch of the experiment using an iterative Broyden's approach. For the purpose of algorithm testing, we first used mathematical surrogates to represent the in vitro experiments and demonstrated five scenarios where the in vitro surrogates are coupled to the computational physiology of a Fontan patient. This testing approach allows validation of the coupling result accuracy as the mathematical surrogates can be directly integrated into the computational simulation to obtain the “true solution” of the coupled system. Our algorithm successfully identified the solution flow waveforms in all test scenarios with results matching the true solutions with high accuracy. In all test cases, the number of iterations to achieve the desired convergence criteria was less than 130. To emulate realistic in vitro experiments in which noise contaminates the measurements, we perturbed the surrogate models by adding random noise. The convergence tolerance achievable with the coupling algorithm remained below the magnitudes of the added noise in all cases. Finally, we used this algorithm to couple a physical experiment to the computational physiology model to demonstrate its real‐world applicability.

    

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3. CTRL: Closed-Loop Transcription to an LDR via Minimaxing Rate Reduction

   https://doi.org/10.3390/e24040456  

   Dai, Xili ; Tong, Shengbang ; Li, Mingyang ; Wu, Ziyang ; Psenka, Michael ; Chan, Kwan Ho ; Zhai, Pengyuan ; Yu, Yaodong ; Yuan, Xiaojun ; Shum, Heung-Yeung ; et al ( April 2022 , Entropy)

   This work proposes a new computational framework for learning a structured generative model for real-world datasets. In particular, we propose to learn a Closed-loop Transcriptionbetween a multi-class, multi-dimensional data distribution and a Linear discriminative representation (CTRL) in the feature space that consists of multiple independent multi-dimensional linear subspaces. In particular, we argue that the optimal encoding and decoding mappings sought can be formulated as a two-player minimax game between the encoder and decoderfor the learned representation. A natural utility function for this game is the so-called rate reduction, a simple information-theoretic measure for distances between mixtures of subspace-like Gaussians in the feature space. Our formulation draws inspiration from closed-loop error feedback from control systems and avoids expensive evaluating and minimizing of approximated distances between arbitrary distributions in either the data space or the feature space. To a large extent, this new formulation unifies the concepts and benefits of Auto-Encoding and GAN and naturally extends them to the settings of learning a both discriminative and generative representation for multi-class and multi-dimensional real-world data. Our extensive experiments on many benchmark imagery datasets demonstrate tremendous potential of this new closed-loop formulation: under fair comparison, visual quality of the learned decoder and classification performance of the encoder is competitive and arguably better than existing methods based on GAN, VAE, or a combination of both. Unlike existing generative models, the so-learned features of the multiple classes are structured instead of hidden: different classes are explicitly mapped onto corresponding independent principal subspaces in the feature space, and diverse visual attributes within each class are modeled by the independent principal components within each subspace. 

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4. Adaptive multi‐rate interface: development and experimental verification for real‐time hybrid simulation

   https://doi.org/10.1002/eqe.2713  

   Maghareh, Amin ; Waldbjørn, Jacob P. ; Dyke, Shirley J. ; Prakash, Arun ; Ozdagli, Ali I. ( February 2016 , Earthquake Engineering & Structural Dynamics)

   Real‐time hybrid simulation (RTHS) is a powerful cyber‐physical technique that is a relatively cost‐effective method to perform global/local system evaluation of structural systems. A major factor that determines the ability of an RTHS to represent true system‐level behavior is the fidelity of the numerical substructure. While the use of higher‐order models increases fidelity of the simulation, it also increases the demand for computational resources. Because RTHS is executed at real‐time, in a conventional RTHS configuration, this increase in computational resources may limit the achievable sampling frequencies and/or introduce delays that can degrade its stability and performance. In this study, the Adaptive Multi‐rate Interface rate‐transitioning and compensation technique is developed to enable the use of more complex numerical models. Such a multi‐rate RTHS is strictly executed at real‐time, although it employs different time steps in the numerical and the physical substructures while including rate‐transitioning to link the components appropriately. Typically, a higher‐order numerical substructure model is solved at larger time intervals, and is coupled with a physical substructure that is driven at smaller time intervals for actuator control purposes. Through a series of simulations, the performance of the AMRI and several existing approaches for multi‐rate RTHS is compared. It is noted that compared with existing methods, AMRI leads to a smaller error, especially at higher ratios of sampling frequency between the numerical and physical substructures and for input signals with high‐frequency content. Further, it does not induce signal chattering at the coupling frequency. The effectiveness of AMRI is also verified experimentally. Copyright © 2016 John Wiley & Sons, Ltd.

    

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5. Physiological responses to gravity in an insect

   https://doi.org/10.1073/pnas.1915424117  

   Harrison, Jon F. ; Adjerid, Khaled ; Kassi, Anelia ; Klok, C. Jaco ; VandenBrooks, John M. ; Duell, Meghan E. ; Campbell, Jacob B. ; Talal, Stav ; Abdo, Christopher D. ; Fezzaa, Kamel ; et al ( January 2020 , Proceedings of the National Academy of Sciences)

   Gravity is one of the most ubiquitous environmental effects on living systems: Cellular and organismal responses to gravity are of central importance to understanding the physiological function of organisms, especially eukaryotes. Gravity has been demonstrated to have strong effects on the closed cardiovascular systems of terrestrial vertebrates, with rapidly responding neural reflexes ensuring proper blood flow despite changes in posture. Invertebrates possess open circulatory systems, which could provide fewer mechanisms to restrict gravity effects on blood flow, suggesting that these species also experience effects of gravity on blood pressure and distribution. However, whether gravity affects the open circulatory systems of invertebrates is unknown, partly due to technical measurement issues associated with small body size. Here we used X-ray imaging, radio-tracing of hemolymph, and micropressure measurements in the American grasshopper,Schistocerca americana, to assess responses to body orientation. Our results show that during changes in body orientation, gravity causes large changes in blood and air distribution, and that body position affects ventilation rate. Remarkably, we also found that insects show similar heart rate responses to body position as vertebrates, and contrasting with the classic understanding of open circulatory systems, have flexible valving systems between thorax and abdomen that can separate pressures. Gravitational effects on invertebrate cardiovascular and respiratory systems are likely to be widely distributed among invertebrates and to have broad influence on morphological and physiological evolution.

    

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