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Hybrid computational modeling methods for systems biology

PROGRESS IN BIOMEDICAL ENGINEERING 2022年第1期4卷

作者： Cruz, Daniel A. Kemp, Melissa L. Georgia Inst Technol Sch Math Atlanta GA 30332 USA Georgia Inst Technol Wallace H Coulter Dept Biomed Engn Atlanta GA 30332 USA Emory Univ Atlanta GA 30322 USA

Systems biology models are typically considered across a spectrum from mechanistic to abstracted description;however, the lines between these forms of modeling are increasingly blurred. Ever-increasing computational power is providing novel opportunities for bridging time and length scales. Furthermore, despite biological mechanisms or network topology often ill-defined, the acquisition of high-throughput data leaves modelers with the desire to leverage available measurements. This review surveys modeling tools in which two or more mathematical forms are blended to describe time-dependent processes in a multivariate system. While most commonly manifested as continuous/discrete description, other forms such as mechanistic/inference or deterministic/stochastic hybrid models can be generated. Recent innovations in hybrid modeling methodologies and new applications illustrate advantages for combining model formats to gaining biological systems level insight.

关键词： computational modeling systems biology simulation prediction

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How infant-directed actions enhance infants' attention, learning, and exploration: Evidence from EEG and computational modeling

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DEVELOPMENTAL SCIENCE 2023年第1期26卷 e13259-e13259页

作者： Meyer, Marlene van Schaik, Johanna E. Poli, Francesco Hunnius, Sabine Radboud Univ Nijmegen Donders Inst Brain Cognit & Behav Thomas van Aquinostr 4 NL-6525 GD Nijmegen Netherlands Univ Chicago Dept Psychol 5848 S Univ Ave Chicago IL 60637 USA Radboud Univ Nijmegen Behav Sci Inst Nijmegen Netherlands

When teaching infants new actions, parents tend to modify their movements. Infants prefer these infant-directed actions (IDAs) over adult-directed actions and learn well from them. Yet, it remains unclear how parents' action modulations capture infants' attention. Typically, making movements larger than usual is thought to draw attention. Recent findings, however, suggest that parents might exploit movement variability to highlight actions. We hypothesized that variability in movement amplitude rather than higher amplitude is capturing infants' attention during IDAs. Using EEG, we measured 15-month-olds' brain activity while they were observing action demonstrations with normal, high, or variable amplitude movements. Infants' theta power (4-5 Hz) in fronto-central channels was compared between conditions. Frontal theta was significantly higher, indicating stronger attentional engagement, in the variable compared to the other conditions. computational modelling showed that infants' frontal theta power was predicted best by how surprising each movement was. Thus, surprise induced by variability in movements rather than large movements alone engages infants' attention during IDAs. Infants with higher theta power for variable movements were more likely to perform actions successfully and to explore objects novel in the context of the given goal. This highlights the brain mechanisms by which IDAs enhance infants' attention, learning, and exploration.

关键词： attention computational modeling EEG infants infant-directed actions surprise theta oscillations variability

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computational modeling of the Effects of Sleep Deprivation on the Vigilance Decrement

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HUMAN FACTORS 2019年第7期61卷 1099-1111页

作者： Patterson, Robert Earl Lochtefeld, Darrell Larson, Kathleen G. Christensen-Salem, Amanda US Air Force Res Lab 711 Human Performance Wing Wright Patterson AFB OH 45433 USA US Air Force Res Lab Airman Syst Directorate Warfighter Interface Div 711 Human Performance Wing Wright Patterson AFB OH 45433 USA US Air Force Res Lab Wright Patterson AFB OH 45433 USA

Objective: We developed a computational model of the effects of sleep deprivation on the vigilance decrement by employing the methods of system dynamics modeling. Background: Situations that require sustained attention for a prolonged duration can cause a decline in cognitive performance, the so-called vigilance decrement. One factor that should influence the vigilance decrement is fatigue in the form of sleep deprivation. Method: We employed the methods of system dynamics modeling (numerical-integration techniques for modeling complex feedback systems) to create a computational model of the vigilance decrement. We then simulated the computational effects of sleep deprivation on the behavior of that model, using empirical data obtained from the literature for calibrating such effects. Results: Sleep deprivation of 2 hr over a 14-day period should produce an additional decline of 9% in detection performance over that found with the typical vigilance decrement, whereas 4 hr of sleep deprivation over 14 days should produce an additional decline of 14% in detection performance. Conclusion: With respect to dual-process theory, it is through its deleterious effects on analytical cognition that sleep deprivation should impact the vigilance decrement. Application: Such computational modeling may be advantageous for human-machine teaming by theoretically allowing a future autonomous software agent to anticipate the decline of human performance and compensate accordingly.

关键词： vigilance computational modeling sleep work-rest cycles

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A review of computational modeling, machine learning and image analysis in cancer metastasis dynamics

Computational and Systems Oncology

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computational and Systems Oncology 2023年第1期3卷

作者： Hirway, Shreyas U. Weinberg, Seth H. Department of Biomedical Engineering The Ohio State University Columbus OH United States

Cancer is a life-threatening process that stems from genetic mutations in cells, which leads to the formation of tumors, and is a major cause of deaths in the United States, with secondary metastasis being a major driver of fatality. The development of an optimal metastatic environment is an essential process prior to tumor metastasis. This process, called pre-metastatic niche formation, involves the activation of resident fibroblast-like cells and macrophages. Tumor-mediated factors introduced to this environment transform resident cells that secrete additional growth factors and remodel the extracellular matrix, which is thought to promote tumor colonization and metastasis in the secondary environment. Furthermore, an important component of metastasis is the biological process of epithelial–mesenchymal transition, which can be exploited by cancer cells to change their phenotype, to migrate and proliferate as necessary. In this review, we discuss recent advances in the investigation of cancer growth and migration. computational models that focus on biochemical signaling and multicellular dynamics are examined. Machine learning models and image analysis that classify cancer-related data are also explored. Through this review, we highlight advances in the study of important aspects of cancer and metastasis signaling and computational tools to study these dynamics. © 2022 The Authors. computational and Systems Oncology published by Wiley Periodicals LLC.

关键词： biochemical signaling cancer computational modeling epithelial–mesenchymal transition image analysis machine learning pre-metastatic niche

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computational modeling of pitting corrosion

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CORROSION REVIEWS 2019年第5期37卷 419-439页

作者： Jafarzadeh, Siavash Chen, Ziguang Bobaru, Florin Univ Nebraska Dept Mech & Mat Engn Lincoln NE 68588 USA Huazhong Univ Sci & Technol Dept Mech Wuhan 430074 Hubei Peoples R China

Pitting corrosion damage is a major problem affecting material strength and may result in difficult to predict catastrophic failure of metallic material systems and structures. computational models have been developed to study and predict the evolution of pitting corrosion with the goal of, in conjunction with experiments, providing insight into pitting processes and their consequences in terms of material reliability. This paper -presents a critical review of the computational models for pitting corrosion. Based on the anodic reaction (dissolution) kinetics at the corrosion front, transport kinetics of ions in the electrolyte inside the pits, and time evolution of the damage (pit growth), these models can be classified into two categories: (1) non-autonomous models that solve a classical transport equation and, separately, solve for the evolution of the pit boundary;and (2) autonomous models like cellular automata, peridynamics, and phase-field models which address the transport, dissolution, and autonomous pit growth in a unified framework. We compare these models with one another and comment on the advantages and disadvantages of each of them. We especially focus on peridynamic and phase-filed models of pitting corrosion. We conclude the paper with a discussion of open areas for future developments.

关键词： cellular automata computational modeling damage peridynamics phase field pitting corrosion

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computational modeling of Ultrasonic Subthalamic Nucleus Stimulation

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 2019年第4期66卷 1155-1164页

作者： Tarnaud, Thomas Joseph, Wout Martens, Luc Tanghe, Emmeric Univ Ghent IMEC INTEC WAVES Dept Informat Technol B-9052 Zwijnaarde Belgium

Objective: To explore the potential of ultrasonic modulation of plateau-potential generating subthalamic nucleus neurons (STN), by modeling their interaction with continuous and pulsed ultrasonic waves. Methods: A computational model for ultrasonic stimulation of the STN is created by combining the Otsuka-model with the bilayer sonophore model. The neuronal response to continuous and pulsed ultrasonic waves is computed in parallel for a range of frequencies, duty cycles, pulse repetition frequencies, and intensities. Results: Ultrasonic intensity in continuous-wave stimulation determines the firing pattern of the STN. Three observed spiking modes in order of increasing intensity are low frequency spiking, high frequency spiking with significant spike-frequency and spike-amplitude adaptation, and a silenced mode. Continuous-wave stimulation has little capability to manipulate the saturated spiking rate in the high frequency spiking mode. In contrast, STN firing rates induced by pulsed ultrasound insonication will saturate to the pulse repetition frequency with short latencies, for sufficiently large intensity and repetition frequency. Conclusion: computational results show that the activity of plateau-potential generating STN can be modulated by selection of the stimulus parameters. Low intensities result in repetitive firing, while higher intensities silence the STN. Pulsed ultrasonic stimulation results in a shorter saturation latency and is able to modulate spiking rates. Significance: Stimulation or suppresion of the STN is important in the treatment of Parkinson's disease, e.g., in deep brain stimulation. This explorative study on ultrasonic modulation of the STN, could be a step in the direction of minimally invasive alternatives to conventional deep brain stimulation.

关键词： Acoustical neurostimulation computational modeling Otsuka-model Subthalamic nucleus (STN) ultrasonic neuromodulation

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computational modeling of convective seepage flow in fluid-saturated heterogeneous rocks: Steady-state approach

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COMPUTERS & GEOSCIENCES 2019年 123卷 103-110页

作者： Zhao, Chongbin Hobbs, B. E. Ord, A. Cent S Univ Computat Geosci Res Ctr Changsha 410083 Hunan Peoples R China Univ Western Australia Sch Earth & Environm Crawley WA 6009 Australia

Convective seepage flow plays a key role not only in naturally forming mineral deposits and oil reservoirs, but also in the carbon-dioxide sequestration in fluid-saturated rocks. This paper presents a steady-state numerical solver, which is based on the finite element method (FEM) and progressive asymptotic approach procedure (PAAP), to solve steady-state convective seepage flow problems in fluid-saturated heterogeneous rocks. Although this kind of flow problem is commonly solved by using transient-state numerical solvers, the use of the proposed steady-state numerical solver, which is the main characteristic of this study, can have certain advantages. After the proposed steady-state numerical solver is verified by a benchmark testing problem, for which analytical solutions are available for comparison, it is further applied to simulate steady-state convective seepage flow in the Australia North West Shelf basin, which is composed of naturally-formed heterogeneous porous rocks. Through the simulated numerical results, it can be found that: (1) compared with the analytical solutions of the benchmark testing problem, the use of the steady-state numerical solver can produce correct and accurate numerical simulation results for dealing with convective seepage flow problems in fluid-saturated heterogeneous rocks. (2) The main advantage of using the steady-state numerical solver is to avoid the need of considering initial conditions of the problem, which are commonly difficult to be determined because the convective seepage flow within the upper crust is a past event in geology. (3) In the Australia North West Shelf basin, the convective seepage flow and temperature distribution patterns depend strongly on both the permeability contrast of the faults and the basin geometry (including the layer structures and fault locations) in the computational model.

关键词： Convective seepage flow computational modeling Finite element method Steady-state solver Porous rock

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Enantioseparation of citalopram enantiomers by capillary electrophoresis: Method development through experimental design and computational modeling

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CHIRALITY 2020年第8期32卷 1119-1128页

作者： Budau, Monica Hancu, Gabriel Muntean, Daniela Lucia Papp, Lajos Attila Carje, Anca Gabriela Garaj, Vladimir Univ Med Pharm Sci & Technol Tirgu Mures Fac Pharm Dept Pharmaceut Chem Gheorghe Marinescu 38 RO-540139 Targu Mures Romania Univ Med Pharm Sci & Technol Tirgu Mures Fac Pharm Dept Analyt Chem & Drug Anal Targu Mures Romania Comenius Univ Fac Pharm Dept Pharmaceut Chem Bratislava Slovakia

Citalopram (CIT) is a frequently used modern antidepressant that inhibits selectively serotonin reuptake in the brain. It has a chiral center in its structure and is used in therapy as both racemic mixture and pure enantiomer as its pharmacological effect is almost entirely associated with S-CIT. The aim of this study was the development of a simple and rapid capillary electrophoresis (CE) method for the separation and quantification of CIT enantiomers. To establish the optimum chiral selector, several native and derivatized, neutral, and ionized cyclodextrins (CDs) were examined at different pH levels. An experimental design strategy was adopted for method optimization;a fractional factorial design was applied for screening purposes to identify significant experimental factors followed by a face-centered central composite design used for optimization purposes. computational modeling was used to obtain information on the interaction energy and the geometry of the complexes to aid in the understanding of chiral separation mechanism. The best results were obtained when using a 25-mM phosphate buffer at pH 7.0, 3-mM CM-beta-CD as chiral selector, 17.5 degrees C temperature, 15-kV voltage, and 50 mbar/s hydrodynamic injection. The separation time was fast, below 3 min, and the migration order was S-CIT followed by R-CIT. The analytical performance of the method was verified in terms of precision, linearity, accuracy, sensibility, and robustness, and the method was applied for the determination of CIT enantiomers from pharmaceutical preparations.

关键词： capillary electrophoresis chiral separation citalopram computational modeling experimental design

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Dissecting the cognitive phenotype of post-stroke fatigue using computerized assessment and computational modeling of sustained attention

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EUROPEAN JOURNAL OF NEUROSCIENCE 2020年第7期52卷 3828-3845页

作者： Ulrichsen, Kristine M. Alnaes, Dag Kolskar, Knut K. Richard, Genevieve Sanders, Anne-Marthe Dorum, Erlend S. Ihle-Hansen, Hege Pedersen, Mads L. Tornas, Sveinung Nordvik, Jan E. Westlye, Lars T. Univ Oslo Inst Clin Med NORMENT Oslo Norway Oslo Univ Hosp Div Mental Hlth & Addict Oslo Norway Univ Oslo Dept Psychol Pb 1094 N-0317 Oslo Norway Sunnaas Rehabil Hosp HF Nesodden Norway Oslo Univ Hosp Dept Neurol Oslo Norway Brown Univ Dept Cognit Linguist & Psychol Sci Providence RI 02912 USA CatoSenteret Rehabil Ctr Son Norway Univ Oslo KG Jebsen Ctr Neurodev Disorders Oslo Norway

Post-stroke fatigue (PSF) is prevalent among stroke patients, but its mechanisms are poorly understood. Many patients with PSF experience cognitive difficulties, but studies aiming to identify cognitive correlates of PSF have been largely inconclusive. With the aim of characterizing the relationship between subjective fatigue and attentional function, we collected behavioral data using the attention network test (ANT) and self-reported fatigue scores using the fatigue severity scale (FSS) from 53 stroke patients. In order to evaluate the utility and added value of computational modeling for delineating specific underpinnings of response time (RT) distributions, we fitted a hierarchical drift diffusion model (hDDM) to the ANT data. Results revealed a relationship between fatigue and RT distributions. Specifically, there was a positive interaction between FSS score and elapsed time on RT. Group analyses suggested that patients without PSF increased speed during the course of the session, while patients with PSF did not. In line with the conventional analyses based on observed RT, the best fitting hDD model identified an interaction between elapsed time and fatigue on non-decision time, suggesting an increase in time needed for stimulus encoding and response execution rather than cognitive information processing and evidence accumulation. These novel results demonstrate the significance of considering the sustained nature of effort when defining the cognitive phenotype of PSF, intuitively indicating that the cognitive phenotype of fatigue entails an increased vulnerability to sustained effort, and suggest that the use of computational approaches offers a further characterization of specific processes underlying behavioral differences.

关键词： attention networks cognitive fatigue computational modeling reaction time rehabilitation stroke sequela

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Predicting the Cardiac Troponin I (cTnl) Aptamer/Methylene Blue Configuration Using computational modeling Studies: A Screening Search Method for Constructing Aptasensors

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CHEMISTRYSELECT 2020年第35期5卷 10958-10969页

作者： Mokhtari, Zaynab Khajehsharifi, Habibollah Hashemnia, Sedigheh Shahrokhian, Saeed Univ Yasuj Dept Chem Yasuj *** Iran Persian Gulf Univ Dept Chem Fac Sci Bushehr 75169 Iran Sharif Univ Technol Dept Chem Tehran 111559516 Iran

Acute Myocardial Infarction (AMI) is the most common cause of mortality, and cardiac troponin I (cTnI) is the gold standard for AMI diagnosis. Some aptamers have been reported to detect cTnI, but there is rarely any structural information on their binding with cTnI. There are many studies involving electrochemical aptasensors with methylene blue (MB) as a redox indicator that does not provide any significant new information. Our study, however, involves the computational modeling of the complexes of a documented 40-mer ssDNA-cTnI aptamer with its target and MB. Here, MB was used as a model system to investigate the rather complex interaction modes between small redox molecules and a cTnI-aptamer. Understanding these modes is an important facet in designing electrochemical aptasensors to ascertain the effectiveness of a redox indicator. In our study, docking and molecular dynamics (MD) were used to provide information on the stability, fluctuations, and interaction analysis of the complexes. Based on computational evaluations, we understand how the structure of the cTnI-aptamer steers the MB releasing after inducing cTnI. In order to evaluate the sensing performance of the cTnI-aptamer in the presence of MB experimentally, after covalent immobilization of the 5-amino terminated cTnI-aptamer at a pre-functionalized carboxylated multi-walled carbon nanotube (COOH-MWCNT) glassy carbon electrode, some techniques including spectroscopy and voltammetry were employed.

关键词： Aptamer computational modeling cTnI Electrochemical aptasensor Methylene blue

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