Teaching physiology within a system dynamics framework

Rubin, David M.; Letts, Robyn F. R.; Richards, Xriz L.

doi:10.1152/advan.00198.2018

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…It will be necessary to bring together these data to understand the physiology of organ systems. Physiology is dynamics ( Rubin et al, 2019 ). Understanding how the function of organs changes over time is essential for understanding both homeostasis for health and disease origins and progression.…”

Section: Introductionmentioning

confidence: 99%

From transcriptomics to digital twins of organ function

Hansen,

Jain,

Nenov

et al. 2024

Front. Cell Dev. Biol.

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Cell level functions underlie tissue and organ physiology. Gene expression patterns offer extensive views of the pathways and processes within and between cells. Single cell transcriptomics provides detailed information on gene expression within cells, cell types, subtypes and their relative proportions in organs. Functional pathways can be scalably connected to physiological functions at the cell and organ levels. Integrating experimentally obtained gene expression patterns with prior knowledge of pathway interactions enables identification of networks underlying whole cell functions such as growth, contractility, and secretion. These pathways can be computationally modeled using differential equations to simulate cell and organ physiological dynamics regulated by gene expression changes. Such computational systems can be thought of as parts of digital twins of organs. Digital twins, at the core, need computational models that represent in detail and simulate how dynamics of pathways and networks give rise to whole cell level physiological functions. Integration of transcriptomic responses and numerical simulations could simulate and predict whole cell functional outputs from transcriptomic data. We developed a computational pipeline that integrates gene expression timelines and systems of coupled differential equations to generate cell-type selective dynamical models. We tested our integrative algorithm on the eicosanoid biosynthesis network in macrophages. Converting transcriptomic changes to a dynamical model allowed us to predict dynamics of prostaglandin and thromboxane synthesis and secretion by macrophages that matched published lipidomics data obtained in the same experiments. Integration of cell-level system biology simulations with genomic and clinical data using a knowledge graph framework will allow us to create explicit predictive models that mechanistically link genomic determinants to organ function. Such integration requires a multi-domain ontological framework to connect genomic determinants to gene expression and cell pathways and functions to organ level phenotypes in healthy and diseased states. These integrated scalable models of tissues and organs as accurate digital twins predict health and disease states for precision medicine.

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Section: Introductionmentioning

confidence: 99%

From transcriptomics to digital twins of organ function

Hansen,

Jain,

Nenov

et al. 2024

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

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“…Students have often used static representations to attempt to gain a better understanding of material presented in a lecture, whether it be drawing it out or diagraming it in a different way (12). However, while useful to help visualize basic functionality of static or linear processes, it can be difficult for students to gain an understanding of the sometimes complex interactions happening within physiology (20).…”

Section: Introductionmentioning

confidence: 99%

Lighting up the NMJ: developing an LED-based model of the neuromuscular junction for the undergraduate classroom

Olson

Turin

Petzold

2020

Advances in Physiology Education

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Many complex physiological processes can be introduced and explored using the framework of the neuromuscular junction (NMJ), including neurotransmitter release, membrane depolarization, and ion channel activity. While traditionally used instructional tools such as static complex drawings are useful, these images can be incomplete physiological representations due to the lack of physically moving parts. As a result, they often misrepresent the complexity of physiological phenomena to students. We describe an effort to create a more accurate, dynamic representation of the NMJ to enhance instruction in an undergraduate anatomy and physiology course. We sought to create a unique and memorable moving diagram that combines elements of static images with moving parts. To evaluate the impact of the dynamic model, students were asked about their understanding of the NMJ before and after exposure to the model. In addition, students were asked for attitudinal responses to the model and their preferred method of instruction. Analysis of student responses indicated that students enjoyed the model, although they also had concerns about the speed of the simulated ion movement being too fast. The model has also served as an informal science education art installation in presentations for prospective students, stakeholders in the broader community, including local and statewide politicians, the University president and board of trustees, donors, and other regional economic and educational leaders.

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Teaching of drug disposition using physiologically based pharmacokinetic modeling software: GastroPlus as an educational tool

Morningstar-Kywi

Morris

Romero

et al. 2023

Advances in Physiology Education

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Physiologically based pharmacokinetic (PBPK) modeling requires understanding of chemical, physiologic, and pharmacokinetic principles. Active learning with PBPK modeling software (GastroPlus®) may be useful to teach these scientific principles while also teaching software operation. To examine this issue, a graduate-level course was designed using learning objectives in science, software use, and PBPK model application. These objectives were taught through hands-on PBPK modeling to answer clinically relevant questions. Students demonstrated proficient use of software, based on their responses to these questions, and showed improved understanding of scientific principles on a pre-/post-course assessment. These outcomes support the effectiveness of simultaneous teaching of interdependent software and science.

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Teaching physiology within a system dynamics framework

Cited by 3 publications

References 7 publications

From transcriptomics to digital twins of organ function

From transcriptomics to digital twins of organ function

Lighting up the NMJ: developing an LED-based model of the neuromuscular junction for the undergraduate classroom

Teaching of drug disposition using physiologically based pharmacokinetic modeling software: GastroPlus as an educational tool

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