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1. An update on an energy-based multiscale modelling framework for physiology.

Author

Hunter, Peter, speaker

Abstract

Bond graphs provide a useful level of abstraction for modelling protein function for a wide range of physiological processes, such as metabolic reactions, membrane transporters, ion channels, myofilament mechanics, receptors and signalling, etc. In this talk I will show how bond graph templates (that conserve mass, charge and energy, respectively) are developed for enzyme-catalysed metabolic reactions, the sodium-potassium ATPase pump, and some of the members of the SLC transporter superfamily (including glucose transport, glutamate transport, sodium-calcium exchange, and sodium-hydrogen exchange). These can be parameterised for a specific cell and tissue type for which the experimental kinetic data is available. I will also show how analytic expressions can be derived for a representative four- or six-state model, given reasonable assumptions associated with steady state flux conditions, while always preserving thermodynamic consistency. Finally, based on work with Weiwei Ai and David Nickerson (Andre), I will present details on fitting parameters for the glucose transporters to experimental data and show how well the steady state flux expressions match the full kinetic analysis.

Published
2024
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2. The Cell Physiome: What do we need in a computational physiology framework for predicting single cell biology?

Author

Rajagopal, Vijay, Arumugam, Senthil, Hunter, Peter, Khadangi, Afshin, Chung, Joshua, and Pan, Michael

Subjects
Quantitative Biology - Cell Behavior, Physics - Biological Physics, Quantitative Biology - Quantitative Methods, Quantitative Biology - Subcellular Processes
Abstract

Modern biology and biomedicine are undergoing a big-data explosion needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome: a framework and approach for creating, sharing, and using biophysics-based computational models of single cell physiology. Using examples in calcium signaling, bioenergetics, and endosomal trafficking, we highlight the need for spatially detailed, biophysics-based computational models to uncover new mechanisms underlying cell biology. We review progress and challenges to date towards creating cell physiome models. We then introduce bond graphs as an efficient way to create cell physiome models that integrate chemical, mechanical, electromagnetic, and thermal processes while maintaining mass and energy balance. Bond graphs enhance modularization and re-usability of computational models of cells at scale. We conclude with a look forward into steps that will help fully realize this exciting new field of mechanistic biomedical data science., Comment: Minor text edits to fix minor grammatical errors and figure reference

Published
2022

7. The SPARC DRC: Building a Resource for the Autonomic Nervous System Community

Author

Osanlouy, Mahyar, Bandrowski, Anita, de Bono, Bernard, Brooks, David, Cassarà, Antonino M, Christie, Richard, Ebrahimi, Nazanin, Gillespie, Tom, Grethe, Jeffrey S, Guercio, Leonardo A, Heal, Maci, Lin, Mabelle, Kuster, Niels, Martone, Maryann E, Neufeld, Esra, Nickerson, David P, Soltani, Elias G, Tappan, Susan, Wagenaar, Joost B, Zhuang, Katie, and Hunter, Peter J

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Neurosciences, Bioengineering, SPARC, autonomic nervous system, FAIR, data curation, data annotation, neural mapping, knowledge management, computational life sciences, Physiology, Medical Physiology, Psychology, Biochemistry and cell biology, Medical physiology
Abstract

The Data and Resource Center (DRC) of the NIH-funded SPARC program is developing databases, connectivity maps, and simulation tools for the mammalian autonomic nervous system. The experimental data and mathematical models supplied to the DRC by the SPARC consortium are curated, annotated and semantically linked via a single knowledgebase. A data portal has been developed that allows discovery of data and models both via semantic search and via an interface that includes Google Map-like 2D flatmaps for displaying connectivity, and 3D anatomical organ scaffolds that provide a common coordinate framework for cross-species comparisons. We discuss examples that illustrate the data pipeline, which includes data upload, curation, segmentation (for image data), registration against the flatmaps and scaffolds, and finally display via the web portal, including the link to freely available online computational facilities that will enable neuromodulation hypotheses to be investigated by the autonomic neuroscience community and device manufacturers.

Published
2021

8. 12 Labours Seminar Series: A multiscale modelling framework for computational physiology

Author

Hunter, Peter, speaker

Abstract

There is much interest from the bioengineering healthcare community worldwide in the concept of a whole-body "digital twin" computational model that can be personalised and linked with data from clinical imaging and hospital-based functional measurements, as well as from a variety of wearable, implantable or home-based devices. To be effective this is going to require a new much more comprehensive and integrative approach to computational physiology. Models of subcellular biology that can take advantage of tissue biomarkers (blood, urine, etc) must be linked with measurements of genotype and included in models of higher-level physiological function at the tissue and organ scale. Surrogate (via machine learning) organ models must be included in organ systems and integrated into whole-body models that include autonomic neural and endocrine control. This talk will discuss the mathematical framework for an algorithmic energy-based approach to multiscale computational physiology that lends itself to crowd-sourcing the international effort needed to tackle the demanding requirements of a "digital" or "virtual" twin for healthcare.

Published
2023
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11. Contributors

Author

Accorsi–Mendonça, Daniela, primary, Adams, David J., additional, Allen, Andrew M., additional, Alvarenga, Marlies, additional, Ardell, Jeffrey L., additional, Arnold, Amy C., additional, Ashton, Jesse L., additional, Badrov, Mark B., additional, Ballantyne, Brennan A., additional, Bardsley, Emma N., additional, Barez-Lopez, Soledad, additional, Barman, Susan M., additional, Barrett, Carolyn J., additional, Bauer, Deborah, additional, Bell, Christopher, additional, Ben-Tal, Alona, additional, Benarroch, Eduardo E., additional, Biaggioni, Italo, additional, Brandl, Katharina, additional, Brooks, Virginia L., additional, Brown, Amy E., additional, Browning, Kirsteen N., additional, Bryarly, Meredith, additional, Camargo, Livia L., additional, Camilleri, Michael, additional, Campbell, Preston J., additional, Caron, Marc G., additional, Carter, Jason R., additional, Chapleau, Mark W., additional, Charkoudian, Nisha, additional, Chelimsky, Gisela, additional, Chelimsky, Thomas C., additional, Chompoopong, Pitcha, additional, Claydon, Victoria E., additional, Clément, Gilles, additional, Convertino, Victor A., additional, Coon, Elizabeth A., additional, Cortelli, Pietro, additional, Davis, Stephen N., additional, Diedrich, André, additional, DiPette, Donald J., additional, Diz, Debra I., additional, Drake, Marcus J., additional, Eisenhofer, Graeme, additional, Elefteriou, Florent, additional, Elijovich, Fernando, additional, Elmenhorst, Eva-Maria, additional, English, Brett A., additional, Esler, Murray, additional, Esler, Rosemary, additional, Fadel, Paul J., additional, Fahrenholz, John M., additional, Fanciulli, Alessandra, additional, Fang, John Y., additional, Fealey, Robert D., additional, Ferreira, Nathanne S., additional, Filogonio, Renato, additional, Fink, Gregory D., additional, Fisher, James P., additional, Floras, John S., additional, Fountain, Samuel J., additional, Fu, Qi, additional, Fudim, Marat, additional, Furlan, Raffaello, additional, Gamboa, Alfredo, additional, Garland, Emily M., additional, Gibbons, Christopher H., additional, Giritharan, Andrew, additional, Goldstein, David S., additional, Golombék, Diego A., additional, Gomez-Sanchez, Elise P., additional, Gomez-Sanchez, Celso E., additional, Graham, Robert M., additional, Grassi, Guido, additional, Greenlund, Ian M., additional, Grubb, Blair P., additional, Guekht, Alla, additional, Guild, Sarah-Jane, additional, Guo, Ling, additional, Gurevich, Vsevolod V., additional, Habermann, Ralf, additional, Hadaya, Joseph, additional, Hahn, Maureen K., additional, Hanna, Peter, additional, Henderson, Luke A., additional, Herring, Neil, additional, Hilz, Max J., additional, Hunter, Peter, additional, Hyland, Keith, additional, Hyland, Lauren A., additional, Jackson, Edwin Kerry, additional, Jacob, Giris, additional, Jänig, Wilfrid, additional, Japundžić-Žigon, Nina, additional, Jones, Carrie K., additional, Joos, Karen M., additional, Jordan, Jens, additional, Joyce, William, additional, Kaidonis, Xenia, additional, Kaufmann, Horacio, additional, Kaye, David, additional, Khan Minhas, Abdul Mannan, additional, Kim, Joyce S., additional, Kitta, Takeya, additional, Kline, David D., additional, Konecny, Thomas, additional, Koons, Natalie J., additional, Kumar, Ambrish, additional, Laffer, Cheryl L., additional, Lagrange, Andre H., additional, Laiken, Nora, additional, Lambert, Gavin, additional, Lambert, Elisabeth, additional, Lamotte, Guillaume, additional, Lenders, Jacques W.M., additional, Levine, Benjamin D., additional, Leys, Fabian, additional, Limper, Ulrich, additional, Lin, Mabelle, additional, Listik, Eduardo, additional, Longmuir, Reid, additional, Low, David A., additional, Low, Phillip A., additional, Luther, James M., additional, Macefield, Vaughan G., additional, Machado, Benedito H., additional, Madel, Maria-Bernadette, additional, Martelli, Davide, additional, Mathias, Christopher J., additional, Mauermann, Michelle L., additional, McAllen, Robin M., additional, McBryde, Fiona D., additional, McKeon, Andrew, additional, McKinley, Michael J., additional, Menuet, Clément, additional, Milam, Douglas F., additional, Mohl, Marion C., additional, Montgomery, Johanna M., additional, Moraes, Davi J.A., additional, Morrison, Shaun F., additional, Murphy, David, additional, Nichols, Charles D., additional, Niewiński, Piotr, additional, Norcliffe-Kaufmann, Lucy, additional, Okamoto, Luis E., additional, Osanlouy, Mahyar, additional, Osborn, John W., additional, Oubaid, Viktor, additional, Palma, Jose-Alberto, additional, Pamporaki, Christina, additional, Parsons, Brian A., additional, Paterson, David J., additional, Paton, Julian F.R., additional, Peltier, Amanda C., additional, Pensato, Umberto, additional, Peterson, Sean M., additional, Phibbs, Fenna T., additional, Pierangeli, Giulia, additional, Potts, Jay D., additional, Rabinstein, Alejandro A., additional, Raizada, Mohan K., additional, Raj, Satish R., additional, Rand, Casey M., additional, Reichmann, Heinz, additional, Robertson, Calum, additional, Robertson, Rose Marie, additional, Robinson, Michael B., additional, Ruzieh, Mohammed, additional, Sandroni, Paola, additional, Sato, Takayuki, additional, Schiffrin, Ernesto L., additional, Schlaich, Markus, additional, Schondorf, Ronald, additional, Schultz, Harold D., additional, Scott, Michael M., additional, Seravalle, Gino, additional, Shannon, John R., additional, Sheikh, Abu Baker, additional, Shibao, Cyndya A., additional, Shivkumar, Kalyanam, additional, Shouman, Kamal, additional, Siepmann, Timo, additional, Singer, Wolfgang, additional, Soltani, Elias, additional, Somers, Virend, additional, Sridharan, Aadhavi, additional, Stefanova, Nadia, additional, Stewart, Julian, additional, Stiles, Lauren E., additional, Sunagawa, Kenji, additional, Tank, Jens, additional, Thijs, Roland D., additional, Tomek, Jakub, additional, Touyz, Rhian M., additional, Tracy, Jennifer A., additional, Travagli, R. Alberto, additional, Undem, Bradley J., additional, Urs, Nikhil, additional, Vernino, Steven, additional, Vianna, Lauro C., additional, Vigo, Daniel E., additional, Vizzard, Margaret A., additional, Wahba, Amr, additional, Waheed, Waqar, additional, Wang, Han-Jun, additional, Wang, Tobias, additional, Wang, Qin, additional, Wang, Ruihao, additional, Weese-Mayer, Debra E., additional, Wenning, Gregor K., additional, Wieling, Wouter, additional, Williams, Kevin W., additional, Winzer-Serhan, Ursula H., additional, Wood, Scott, additional, Yap, Kai Lee, additional, Yoshimura, Naoki, additional, Zavalin, Kirill A., additional, Zhuravlev, Dmitry, additional, Zoccal, Daniel B., additional, and Zubcevic, Jasenka, additional

Published
2023
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15. FieldML

Author

Britten, Randall D., Hunter, Peter, Nielsen, Poul M. F., Miller, Andrew K., Bradley, Chris, Christie, G. Richard, Migliore, Michele, Section editor, Linster, Christiane, Section editor, Cavarretta, Francesco, Section editor, Jaeger, Dieter, editor, and Jung, Ranu, editor

Published
2022
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18. A Narrative Review of Personalized Musculoskeletal Modeling Using the Physiome and Musculoskeletal Atlas Projects.

Author

Fernandez, Justin, Shim, Vickie, Schneider, Marco, Choisne, Julie, Handsfield, Geoff, Yeung, Ted, Zhang, Ju, Hunter, Peter, and Besier, Thor

Subjects
BIOLOGICAL models, COMPUTER simulation, REFERENCE books, KNEE joint, ACHILLES tendon, SKELETAL muscle, COMPUTER-aided design, BIOINFORMATICS, CALF muscles, STATISTICAL models, CARPOMETACARPAL joints
Abstract

In this narrative review, we explore developments in the field of computational musculoskeletal model personalization using the Physiome and Musculoskeletal Atlas Projects. Model geometry personalization; statistical shape modeling; and its impact on segmentation, classification, and model creation are explored. Examples include the trapeziometacarpal and tibiofemoral joints, Achilles tendon, gastrocnemius muscle, and pediatric lower limb bones. Finally, a more general approach to model personalization is discussed based on the idea of multiscale personalization called scaffolds. [ABSTRACT FROM AUTHOR]

Published
2023
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19. Physiome Repository

Author

Yu, Tommy, Britten, Randall D., Nickerson, David P., Hunter, Peter, Nielsen, Poul M. F., Migliore, Michele, Section editor, Linster, Christiane, Section editor, Cavarretta, Francesco, Section editor, Jaeger, Dieter, editor, and Jung, Ranu, editor

Published
2022
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22. 12 Labours Seminar Series (Platform 1): A framework for personalised Physiome modelling

Author

Hunter, Peter, speaker

Abstract

Most human disease (chronic or susceptibility to a virus) seems to have about a 50:50 mix of genetic predisposition and 'environmental' (i.e. non-genetic) association. The MBIE-funded 12 Labours project is attempting to bring both of these factors to bear on three specific medical challenges (the three Exemplar Projects) by building three technology platforms - P1: multiscale modelling; P2: model-based clinical workflows; and P3: a common infrastructure for handing data from wearable and implantable devices. The talk will address one aspect of this challenge for P1. Namely, how do we create a modelling infrastructure that can connect multiscale gene/protein/cell/tissue/organ models with anatomical systems that involve the whole body: the cardiovascular system, the autonomic nervous system, the enteric nervous system, the epithelial integumentary system, the lymphatic system, and the musculoskeletal system (for force transmission). We certainly do not have all the answers to this challenge, but we are beginning to construct what we call 'functional connectivity' maps that we think will help link this whole body connectivity with our standards-based infrastructure for multiscale modelling (based on the CellML and FieldML standards that ABI has pioneered).

Published
2022
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23. Genomic dissection of Klebsiella pneumoniae infections in hospital patients reveals insights into an opportunistic pathogen

Author

Gorrie, Claire L., Mirčeta, Mirjana, Wick, Ryan R., Judd, Louise M., Lam, Margaret M. C., Gomi, Ryota, Abbott, Iain J., Thomson, Nicholas R., Strugnell, Richard A., Pratt, Nigel F., Garlick, Jill S., Watson, Kerrie M., Hunter, Peter C., Pilcher, David V., McGloughlin, Steve A., Spelman, Denis W., Wyres, Kelly L., Jenney, Adam W. J., and Holt, Kathryn E.

Published
2022
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28. Why Aquinas Would Agree That Human Economic Behaviour Is Largely Predictable

Author

Conrad, Richard, Hunter, Peter, Róna, Peter, Series Editor, Zsolnai, László, Series Editor, Alford, Helen, Editorial Board Member, Bouckaert, Luk, Editorial Board Member, Bruni, Luigino, Editorial Board Member, Enderle, Georges, Editorial Board Member, Hoevel, Carlos, Editorial Board Member, Loughlin, John, Editorial Board Member, Miller, David W., Editorial Board Member, Mukherjee, Sanjoy, Editorial Board Member, Thompson, Mike, Editorial Board Member, Verstraeten, Johan, Editorial Board Member, and Zamagni, Stefano, Editorial Board Member

Published
2020
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32. ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters

Author

Pahlevan, Nima, Mangin, Antoine, Balasubramanian, Sundarabalan V., Smith, Brandon, Alikas, Krista, Arai, Kohei, Barbosa, Claudio, Bélanger, Simon, Binding, Caren, Bresciani, Mariano, Giardino, Claudia, Gurlin, Daniela, Fan, Yongzhen, Harmel, Tristan, Hunter, Peter, Ishikaza, Joji, Kratzer, Susanne, Lehmann, Moritz K., Ligi, Martin, Ma, Ronghua, Martin-Lauzer, François-Régis, Olmanson, Leif, Oppelt, Natascha, Pan, Yanqun, Peters, Steef, Reynaud, Nathalie, Sander de Carvalho, Lino A., Simis, Stefan, Spyrakos, Evangelos, Steinmetz, François, Stelzer, Kerstin, Sterckx, Sindy, Tormos, Thierry, Tyler, Andrew, Vanhellemont, Quinten, and Warren, Mark

Published
2021
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34. 12 Labours Seminar Series: Overview of 12 Labours project and multiscale modelling

Author

Hunter, Peter, speaker

Abstract

The ABI is leading the [International Physiome Project](https://www.iups.org/activities/physiome/) for the International Union of Physiological Sciences (IUPS) and it is a founding member of the Virtual Physiological Human (VPH) Institute [VPH Institute](https://www.vph-institute.org), an international non-profit organisation, whose mission is to ensure that the Virtual Physiological Human is fully realised, universally adopted, and effectively used both in research and clinic. The Physiome Project aims to establish a standards-based framework for multiscale computational physiology and has established the Physiome journal and associated portal in support of this aim. A five year project has recently been funded by the NZ Government’s Ministry of Business, Innovation and Employment (MBIE) to extend the Physiome Project infrastructure and to develop clinical workflows based around three ‘exemplar projects’ using three underpinning technology platforms as described below. The overall goal for the 12 Labours project is to further develop the predictive modelling capability that ABI and its international partners have built in the Physiome Project, and to add personalised modelling and various forms of wearable or implantable device to assist in the clinical diagnosis and treatment of a range of medical conditions. All software and models are open source and freely available as our contribution to open science but we are also looking for opportunities to create spinout companies that facilitate the clinical uptake of our science. As described below, we will use three exemplar projects (EPs) to demonstrate healthcare applications of multiscale biophysically based modelling, by combining multiscale models of multiple organ systems to address complex physiological questions. These three exemplars are: - *EP1: Pulmonary hypertension*: this exemplar will couple our previously independent research on the cardiovascular and respiratory systems to treat pulmonary hypertension. - *EP2: Personalised rehabilitation of upper limb disorders*: based on our neuro-musculoskeletal system work that is closely linked with the ICON project co-funded by the German Government. - *EP3: Control of organ function by the autonomic nervous system*: based on coupling our previously independent work on maternal health and the digestive system with our NIH-funded work on mapping the autonomic nervous system. The three technology platforms being developed are: - *Platform 1: A framework for personalised Physiome modelling*. We will develop the tools and databases needed to combine models, to link models across spatial and temporal scales, and to personalise the models ready to be used by the EPs in platforms 2 and 3. - *Platform 2: A Physiome modelling platform for precision medicine*. We will develop the workflows and databases needed to implement personalised Physiome models in a clinical setting. - *Platform 3: Continuous monitoring using Physiome workflows*. We will develop an interface between personalised Physiome models and wearable, implanted and home-based devices that can provide a continuous flow of data to update an individual’s personalised model for diagnostic monitoring and predicting therapeutic outcomes. Under 12 Labours, the multiscale models developed in the Physiome Project will be personalised for an individual with the tools developed in Platform 1, incorporated into clinical workflows in Platform 2, and interfaced to home-based healthcare devices in Platform 3.

Published
2021
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35. Resolving phytoplankton pigments from spectral images using convolutional neural networks

Author

Salmi, Pauliina, Pölönen, Ilkka, Beckmann, Daniel Atton, Calderini, Marco L., May, Linda, Olszewska, Justyna, Perozzi, Laura, Pääkkönen, Salli, Taipale, Sami, Hunter, Peter, Salmi, Pauliina, Pölönen, Ilkka, Beckmann, Daniel Atton, Calderini, Marco L., May, Linda, Olszewska, Justyna, Perozzi, Laura, Pääkkönen, Salli, Taipale, Sami, and Hunter, Peter

Abstract

Motivated by the need for rapid and robust monitoring of phytoplankton in inland waters, this article introduces a protocol based on a mobile spectral imager for assessing phytoplankton pigments from water samples. The protocol includes (1) sample concentrating; (2) spectral imaging; and (3) convolutional neural networks (CNNs) to resolve concentrations of chlorophyll a (Chl a), carotenoids, and phycocyanin. The protocol was demonstrated with samples from 20 lakes across Scotland, with special emphasis on Loch Leven where blooms of cyanobacteria are frequent. In parallel, samples were prepared for reference observations of Chl a and carotenoids by high-performance liquid chromatography and of phycocyanin by spectrophotometry. Robustness of the CNNs were investigated by excluding each lake from model trainings one at a time and using the excluded data as independent test data. For Loch Leven, median absolute percentage difference (MAPD) was 15% for Chl a and 36% for carotenoids. MAPD in estimated phycocyanin concentration was high (102%); however, the system was able to indicate the possibility of a cyanobacteria bloom. In the leave-one-out tests with the other lakes, MAPD was 26% for Chl a, 27% for carotenoids, and 75% for phycocyanin. The higher error for phycocyanin was likely due to variation in the data distribution and reference observations. It was concluded that this protocol could support phytoplankton monitoring by using Chl a and carotenoids as proxies for biomass. Greater focus on the distribution and volume of the training data would improve the phycocyanin estimates.

Published
2024

39. Musculoskeletal Modelling and the Physiome Project

Author

Fernandez, Justin, Zhang, Ju, Shim, Vickie, Munro, Jacob T., Sartori, Massimo, Besier, Thor, Lloyd, David G., Nickerson, David P., Hunter, Peter, Serafini, Paolo, Series editor, Guazzelli, Elisabeth, Series editor, Schrefler, Bernhard, Series editor, Pfeiffer, Friedrich, Series editor, Rammerstorfer, Franz G., Series editor, and Pivonka, Peter, editor

Published
2018
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41. Cover Image, Volume 531, Issue 16

Author

Ma, Jichao, primary, Nguyen, Duyen, additional, Madas, Jazune, additional, Bizanti, Ariege, additional, Mistareehi, Anas, additional, Kwiat, Andrew M., additional, Chen, Jin, additional, Lin, Mabelle, additional, Christie, Richard, additional, Hunter, Peter, additional, Heal, Maci, additional, Baldwin, Shane, additional, Tappan, Susan, additional, Furness, John B., additional, Powley, Terry L., additional, and Cheng, Zixi (Jack), additional

Published
2023
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43. Optical types of inland and coastal waters

Author

Spyrakos, Evangelos, O’Donnell, Ruth, Hunter, Peter D., Miller, Claire, Scott, Marian, Simis, Stefan G. H., Neil, Claire, Barbosa, Claudio C. F., Binding, Caren E., Bradt, Shane, Bresciani, Mariano, Dall’Olmo, Giorgio, Giardino, Claudia, Gitelson, Anatoly A., Kutser, Tiit, Li, Lin, Matsushita, Bunkei, Martinez-Vicente, Victor, Matthews, Mark W., Ogashawara, Igor, Ruiz-Verdú, Antonio, Schalles, John F., Tebbs, Emma, Zhang, Yunlin, and Tyler, Andrew N.

Published
2018

46. Modelling Respiration Induced Torso Deformation Using a Mesh Fitting Algorithm

Author

Yu, Haobo, Ho, Harvey, Bartlett, Adam, Hunter, Peter, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chen, Chu-Song, editor, Lu, Jiwen, editor, and Ma, Kai-Kuang, editor

Published
2017
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48. The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart

Author

Fonseca, Carissa G, Backhaus, Michael, Bluemke, David A, Britten, Randall D, Do Chung, Jae, Cowan, Brett R, Dinov, Ivo D, Finn, J Paul, Hunter, Peter J, Kadish, Alan H, Lee, Daniel C, Lima, Joao AC, Medrano−Gracia, Pau, Shivkumar, Kalyanam, Suinesiaputra, Avan, Tao, Wenchao, and Young, Alistair A

Subjects
Networking and Information Technology R&D (NITRD), Heart Disease, Biomedical Imaging, Bioengineering, Cardiovascular, Aged, Aged, 80 and over, Atlases as Topic, Cardiovascular Diseases, Computational Biology, Databases, Factual, Diagnostic Imaging, Female, Heart, Humans, Magnetic Resonance Imaging, Cine, Male, Middle Aged, Models, Cardiovascular, Models, Statistical, Myocardium, Software, Mathematical Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

MotivationIntegrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups.ResultsThree main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt).Availabilityhttp://www.cardiacatlas.orgContacta.young@auckland.ac.nzSupplementary informationSupplementary data are available at Bioinformatics online.

Published
2011

50. Remote sensing in shallow lake ecology

Author

Hunter, Peter D., Tyler, Andrew N., Willby, Nigel, and Gilvear, David

Subjects
577.6309796, Remote sensing, Limnology, Water quality, Water framework directive, Aquatic botany, Phycology, Ecophysiology, Remote sensing, Limnology, Eutrophication, Lake ecology Great Britain, Lake ecology Europe
Abstract

Shallow lakes are an important ecological and socio-economic resource. However, the impact of human pressures, both at the lake and catchment scale, has precipitated a decline in the ecological status of many shallow lakes, both in the UK, and throughout Europe. There is now, as direct consequence, unprecedented interest in the assessment and monitoring of ecological status and trajectory in shallow lakes, not least in response to the European Union Water Framework Directive (2000/60/EC). In this context, the spatially-resolving and panoramic data provided by remote sensing platforms may be of immense value in the construction of effective and efficient strategies for the assessment and monitoring of ecological status in shallow lakes and, moreover, in providing new, spatially-explicit, insights into the function of these ecosystems and how they respond to change. This thesis examined the use of remote sensing data for the assessment of (i) phytoplankton abundance and species composition and (ii) aquatic vegetation distribution and ecophysiological status in shallow lakes with a view to establishing the credence of such an approach and its value in limnological research and monitoring activities. High resolution in-situ and airborne remote sensing data was collected during a 2-year sampling campaign in the shallow lakes of the Norfolk Broads. It was demonstrated that semi-empirical algorithms could be formulated and used to provide accurate and robust estimations of the concentration of chlorophyll-a, even in these optically-complex waters. It was further shown that it was possible to differentiate and quantify the abundance of cyanobacteria using the biomarker pigment C-phycocyanin. The subsequent calibration of the imagery obtained from the airborne reconnaissance missions permitted the construction of diurnal and seasonal regional-scale time-series of phytoplankton dynamics in the Norfolk Broads. This approach was able to deliver unique spatial insights into the migratory behaviour of a potentially-toxic cyanobacterial bloom. It was further shown that remote sensing can be used to map the distribution of aquatic plants in shallow lakes, importantly including the extent of submerged vegetation, which is central to the assessment of ecological status. This research theme was subsequently extended in an exploration of the use of remote sensing for assessing the ecophysiological response of wetland plants to nutrient enrichment. It was shown that remote sensing metrics could be constructed for the quantification of plant vigour. The extrapolation of these techniques enabled spatial heterogeneity in the ecophysiological response of Phragmites australis to lake nutrient enrichment to be characterised and assisted the formulation of a mechanistic explanation for the variation in reedswamp performance in these shallow lakes. It is therefore argued that the spatially synoptic data provided by remote sensing has much to offer the assessment, monitoring and policing of ecological status in shallow lakes and, in particular, for facilitating the development of pan-European scale lake surveillance capabilities for the Water Framework Directive (2000/60/EC). It is also suggested that remote sensing can make a valuable contribution to furthering ecological understanding and, most significantly, in enabling ecosystem processes and functions to be examined at the lake-scale.

Published
2007

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