@conference {
	title = {Modeling the Alzheimer{\textquoteright}s Disease Network},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2015},
	month = {06/2015},
	address = {Antibes - Juan les Pins France},
	booktitle = {1st International Conference on Mathematical NeuroScience (ICMNS 2015)}
}
@conference {
	title = {The glymphatic system and Alzheimer{\textquoteright}s disease: possible connection?},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2014},
	month = {04/2014},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is the most common cause of dementia in the elderly, accounting for 60-80\% of all dementias. Symptoms of AD include memory loss (initially short term, later on long term as well), changes in mood and sun-downing. Magnetic resonance imaging (MRI) shows diffuse cortical atrophy and enlargement of the lateral ventricles due to neuronal cell loss. At the cellular level, neuroinflammation, activation of microglia, deposition of beta amyloid (Aβ) in the brain parenchyma and cerebral vasculature, and increases in the permeability of the bloodbrain barrier (BBB) have all been observed as well. A newly developed theory purports that the glymphatic system of the brain may play a significant role in AD pathogenesis. This paper presents an initial mathematical model of the glymphatic system and studies how changes of transporter density and deposition of Aβ at the BBB changes clearance of Aβ. Changes in local neuronal cell density were also modeled. This represents one of the first attempts to computationally study the role of the glymphatic system in AD.},
	address = {Chamonix, France},
	booktitle = {Biotechno 2014},
	pages = {pp. 15-19}
}
@conference {
	title = {Cerebral vasculature, Alzheimer{\textquoteright}s disease and cerebral amyloid angiopathy: What is the Connection:  A Mathematical Model},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2013},
	month = {11/2013},
	address = {San Diego, CA},
	booktitle = {6th International IEEE EMBS Conference on Neural Engineering}
}
@conference {
	title = {Studying the role of Apoe in Alzheimer{\textquoteright}s disease pathogenesis using a systems biology model},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2013},
	month = {03/2013},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is the most common form of dementia. Even with its well-known symptoms of memory loss and well-characterized pathology of beta amyloid (A) plaques and neurofibrillary tangles, the disease pathogenesis and initiating factors are still not well understood. To tackle this problem, a systems biology model has been developed and used to study the varying effects of variations in the ApoE allele present, as well as the effects of short term and periodic inflammation at low to moderate levels. Simulations showed a late onset peak of A in the ApoE4 case that lead to localized neuron loss which could be ameliorated in part by application of short-term pro-inflammatory mediators. The model that has been developed herein represents one of the first attempts to model AD from a systems approach to study physiologically relevant parameters that may prove useful to physicians in the future.},
	address = {Honolulu, Hawaii},
	booktitle = {5th International Conference on Bioinformatics and Computational Biology (BICoB)},
	pages = {pp. 1342003-1 -1342003-21}
}
@conference {
	title = {A Graph Theoretic Mathematical Model for Alzheimer{\textquoteright}s Disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2012},
	month = {11/2012},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is currently the most common form of dementia affecting the elderly, and its occurrence rate is only expected to increase over the next several decades. Though there is a vast array of knowledge about individual molecules and genetics involved with the disease, there is no clear understanding of the mechanism of pathogenesis. To help better understand the disease process, a graph theoretic model was developed that studies both the concentration of molecules thought to be involved in pathogenesis (Aβ, interleukin1, tumor necrosis factor alpha, cholesterol, ATP levels), as well as the cell number in a small location in the brain. Particular emphasis was put on the role of the inflammatory process in AD progression. This represents one of the first models that uses graph theory combined with a systems biology approach to study AD.},
	address = {Larnaca, Cyprus},
	booktitle = {12th IEEE International Conference on BioInformatics and BioEngineering},
	pages = {pp. 472-477}
}
@conference {
	title = {Inflammation and Cholesterol: Friend Or Foe in Alzheimer{\textquoteright}s Disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2012},
	month = {08/2012},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is the most common form of dementia affecting the elderly, leading to debilitating memory loss and significant cognitive decline. The exact mechanism of pathogenesis is not well understood. Here, we present an organ level model that studies the role of cholesterol metabolism and inflammation in the early stages of AD, demonstrating the importance of brain cholesterol on the expression of beta amyloid. The model has been further validated with experimental data.},
	address = {San Diego, California},
	booktitle = {SIAM Conference on the Life Sciences 2012}
}
@conference {
	title = {Understanding Alzheimer{\textquoteright}s disease with Network Biology},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2012},
	month = {03/2012},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is a complex disease showing dysregulation of several key pathways and an abnormal increase in levels of beta amyloid (Aβ) and hyperphosphorylated tau. Although AD is the most common type of memory loss among the elderly, its pathogenesis is not well understood. Mathematical modeling offers a unique opportunity to gain a better understanding of the AD disease process by combining the current knowledge within a quantitative framework. Using a network model for AD, we discuss how the transition from a normal, healthy brain to an AD brain network can be modeled using a Markov model.},
	address = {Philadelphia, PA},
	booktitle = {The 2012 Northeast Bioengineering Conference (NEBEC 2012)},
	pages = {pp. 67-68},
	organization = {Temple University}
}
@conference {
	title = {A Systems Biology Model Studying the Role of Cholesterol in Alzheimer{\textquoteright}s Disease Progression},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2011},
	month = {10/2011},
	abstract = {A simplified network describing the interactions between the cholesterol and beta amyloid (Aβ) synthesis pathways was generated using information available from literature and the KEGG database. A system of non-linear differential equations was developed and modeled using several different initial conditions. Rate constants were approximated using ratiometric data from the literature, or by fitting parameters to obtain a stable simulation within given biological constraints. Simulations demonstrated the importance of negative feedback control by cholesterol in the regulation of beta-amyloid levels. Additionally, the effect of reduced LRP-1 levels and oscillatory cholesterol generation was studied.},
	address = {Kos Island, Greece},
	booktitle = {10th IEEE International Workshop on Biomedical Engineering (10thBioEng)},
	pages = {pp. 1-7}
}
@conference {
	title = {A systems biology model studying the role of cholesterol in Alzheimer{\textquoteright}s disease progression},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2011},
	month = {08/2011},
	abstract = {A simplified network describing the interactions between the cholesterol and beta amyloid (Aβ) synthesis pathways was generated using information available from literature and the KEGG database.~ A system of non-linear differential equations was developed and modeled using several different initial conditions.~ Rate constants were approximated using ratio-metric data from the literature, or by fitting parameters to obtain a stable simulation within given biological constraints.~ Simulations demonstrated the importance of negative feedback control by cholesterol in the regulation of beta-amyloid levels.~ Additionally, the effect of reduced LRP-1 levels and oscillatory cholesterol generation was studied.~},
	address = {Chicago, Illinois},
	booktitle = {ACM Conference on Bioinformatics, Computational Biology and~Biomedicine 2011}
}
@conference {
	title = {Studying Alzeihmer{\textquoteright}s disease pathogenesis using a systems biology approach},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2011},
	month = {07/2011},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is the most common form of dementia among the elderly, affecting approximately 1 in 6 individuals over the age of 65. To help study the progression of AD, we have developed a mixed metabolic-lipidomic-proteomic network to represent the key interactions in pathways that have been linked to AD. We will present simulation results which study how robust feedback plays an important role in the disease process, as well as how varying cholesterol and LRP concentration levels affects the level of beta amyloid in the system, such as is seen in AD.},
	address = {Seattle, Washington},
	booktitle = {Systems Biology Symposium 2011 (ISB 2011)}
}
@conference {
	title = {Modeling Alzheimer{\textquoteright}s Disease Using A Systems Biology Approach},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2011},
	month = {03/2011},
	abstract = {Alzheimers disease (AD) is the most common form of dementia afflicting the elderly today and is believed to be caused by the buildup of the beta amyloid protein (A{\ss}) within the brain and cerebral vasculature. Although a vast amount of knowledge exists, there is currently no definitive understanding of the initiating factor and subsequent pathogenesis, partially due to the difficulty in directly studying or manipulating the brain experimentally. To overcome this problem, we have developed a systems-level network that encompasses metabolic, lipidomic, and proteomic network topologies, taking into account known feedback and regulation mechanisms. By studying the interactions between the different networks computationally, we have identified several nodes which may be key for initiating a change from a healthy network state to a disease state. We have also performed in vivo experiments in APP/Swe/PS1 transgenic mice to study the effect of simvastatin, a cholesterol inhibitor and potent anti-inflammatory, on the expression levels of A{\ss}, APP, LRP-1 and apoE. These experiments, in combination with our computational model, help to identify crucial feedback points and provide the first known attempt to model AD from a systems-level standpoint.},
	address = {Baltimore, MD},
	booktitle = {Proceedings of the 2011 Biophysical Society}
}
@conference {
	title = {A systems biology model studying the role of cholesterol in Alzheimer{\textquoteright}s disease pathogenesis},
	author = {Kyrtsos, C Rose., Lee, Hey-Kyoung., Baras, John S.},
	year = {2010},
	month = {11/2010},
	abstract = {Objective: To develop a systems-level, metabolic network model to study the effect that alterations in the brain cholesterol concentration levels have on downstream or interconnected sub-networks in an Alzheimer{\textquoteright}s disease (AD) model.Methods: A simplified network encompassing both basic metabolic networks such as glucose and amino acid metabolism, as well as APP processing, cholesterol metabolism, and cholesterol-related metabolic pathways was generated using pathways described by either the KEGG database or in the literature. A differential equations model describing the distribution of molecules within the network over time was developed and simulated using Matlab. The model was initialized using healthy concentrations of all pertinent and known quantities. Individual molecules were represented by nodes in the topological mapping, while reactions between different molecules were designated by weighted links. The weights of the links were determined stoichiometrically, where possible, or statistically, if data was not available.Results: Our results are one of the first attempts to study Alzheimer{\textquoteright}s disease using a systems biology approach. This approach is unique in that it allows us to merge the creation of a systems-level quantitative model for the brain metabolic network with data obtained from in vivo experiments to generate the most accurate mathematical model using current knowledge. The topology of the initially-generated network showed crucial overlap between the APP clearance pathway and cholesterol distribution pathway in adults, specifically with the shared usage of apolipoprotein E (apoE) as a carrier for both beta amyloid (Aβ) cholesterol, and with the LDL receptor-related protein (LRP-1) as a necessary transport protein for Aβ out of the brain and cholesterol into neurons. Short run simulations of networks with decreased brain cholesterol synthesis showed slight increases in the concentration levels of Aβ.Conclusion: We have developed a systems-level, pseudo-metabolic network for the basic metabolic pathways in the brain that are pertinent to the development of AD. Analysis of the network structure revealed several important topological homologies between APP and cholesterol processing. Given our results and the important role that cholesterol plays in maintaining normal neuronal function, it is likely that decreased cholesterol will negatively affect functioning of neurons. Our future work will use an in vivo mouse model to study the effects of decreased brain cholesterol on AD pathology.},
	address = {San Diego, CA},
	booktitle = {40th Annual Meeting Neuroscience 2010}
}
@conference {
	title = {The Role of Cholesterol in Alzheimer{\textquoteright}s disease Pathogenesis: Preliminary Report},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {10/2010},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is a devastating neurodegenerative disorder affecting 1 in 8 individual over the age of 65. A growing body of evidence is suggesting that cholesterol levels in both the brain and the plasma may play significant roles in AD pathogenesis; however, the exact nature of this role is currently not well understood. Building on previous experiments, we have approached this problem using two, complementary methods- a systems biology model for brain metabolic networks that is based on empirical data gathered from in vivo experiments. The main goal of this study was to determine the effect that decreased brain cholesterol had on the level of beta amyloid (the key protein implicated in AD pathogenesis) and the extent of neurodegeneration observed. To achieve this, APPSwe/PS1 double transgenic mice were treated twice daily with simvastatin (a cholesterol-lowering drug) for a period of 2 or 10 weeks. The effects of the decreased brain cholesterol levels on APP and beta amyloid processing, as well as apoE and LRP-1 expression levels was studied using Western blotting and immunohistochemistry techniques, respectively. The extent of neurodegeneration was determined via immunohistochemical staining of hippocampal slices for synaptic density and neuron viability. The weights between key nodes in the systems biology model were updated to account for the observed experimental results.},
	address = {Austin, Texas},
	booktitle = {Biomedical Engineering Society (BMES 2010)}
}
@conference {
	title = {A Network Model of Alzheimer{\textquoteright}s disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {07/2010},
	abstract = {We have derived a multi-scale network model to study the relationship between cholesterol and Aβ in silico to integrate with future experimental work. A pseudo-metabolic network approach has been taken to model the interactions between various signaling molecules, carrier and transport proteins, as well as other proteins that are considered pertinent to AD pathogenesis. We have also monitored the number of neurons and related synapses using a modified McCulloch-Pitts neural network.},
	address = {Pittsburgh, Pennsylvania},
	booktitle = {2010 SIAM Life Sciences Conference}
}
@conference {
	title = {A Systems Biology Approach to Understanding Alzheimer{\textquoteright}s Disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {04/2010},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is the most prevalent form of dementia affecting the elderly. AD has devastating effects on the individual, leading to neuronal and synaptic loss, neuroinflammation, dysfunction of the blood-brain barrier and deposition of amyloid beta plaques in the brain parenchyma and cerebral blood vessels. Due to the inherent difficulty studying the many possible initiating factors of AD with in vivo models, we have chosen to approach this problem from a quantitative perspective initially to determine what key factors may initiate AD pathogenesis. We have developed a multi-scale systems biology model that describes the interactions between different components of the brain{\textquoteright}s biological network at the tissue, cellular and transcriptional levels. Neurons have been modeled using a modified McCulloch-Pitts neural network that accounts for cell death and synapse loss due to varying amyloid beta and cholesterol levels. Microglia have been modeled in both the ramified and activated states using the Langevin equations of motion. The spatial-temporal distribution of beta amyloid has been modeled using the convection-reaction-diffusion equation with stochastic generation rates. Transport of beta amyloid by LRP-1 across the blood-brain barrier has also been modeled. Future generations of the model will take into account experimental results, as well as include models for plaque development in the basement membrane of cerebral blood vessels.},
	address = {College Park, Maryland},
	booktitle = {2010 Southern Biomedical Engineering Conference},
	organization = {University of Maryland}
}
@conference {
	title = {A Mathematical Model for Alzheimer{\textquoteright}s disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {02/2010},
	abstract = {A mathematical model for Alzheimer{\textquoteright}s disease (AD) has been developed using a systems biology approach. A cellular network of neurons, microglia and astrocytes has been created to model the levels of Aβ in the brain. The production and spatial distribution of beta amyloid (Aβ), the key protein implicated in AD, has been modeled using the reaction-diffusion equation, where reaction rates have been modeled using stochastic functions. Neurons have been modeled using a previously developed McCulloch-Pitts neural network (Butz 2006) modified to account for neuronal cell death and loss of synaptic elements during high Aβ levels. Microglia are either in the ramified state (at rest) and modeled using a continuous random walk model, or in the activated state (actively moving towards a source of Aβ) and modeled using the Langevin equation of motion. Astrocytes are defined to set locations and contribute to removal of Aβ from the brain interstitial fluid. The roles that local cerebral blood flow, transport across the BBB, and local reactions play have also been modeled. Future work will look at the development of amyloid beta plaques in the cerebrovasculature and brain parenchyma, and their relationship to observed decreases in cerebral blood flow as the disease progresses.},
	address = {San Francisco, California},
	booktitle = {Proceddings of the 2010 Biophysical Society Annual Meeting}
}
@conference {
	title = {A Systems Biology Approach to Modelling Alzheimer{\textquoteright}s disease},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2010},
	month = {01/2010},
	abstract = {A mathematical model for Alzheimer{\textquoteright}s disease (AD) has been developed using a systems biology approach. A cellular network of neurons, microglia and astrocytes has been created to model the levels of Aβ in the brain. The production and spatial distribution of beta amyloid (Aβ), the key protein implicated in AD, has been modeled using the reaction-diffusion equation, where reaction rates have been modeled using stochastic functions. Neurons have been modeled using a previously developed McCulloch-Pitts neural network (Butz 2006) modified to account for neuronal cell death and loss of synaptic elements during high Aβ levels. Microglia are either in the ramified state (at rest) and modeled using a continuous random walk model, or in the activated state (actively moving towards a source of Aβ) and modeled using the Langevin equation of motion. Astrocytes are defined to set locations and contribute to removal of Aβ from the brain interstitial fluid. The roles that local cerebral blood flow, transport across the BBB, and local reactions play have also been modeled. Future work will look at the development of amyloid beta plaques in the cerebrovasculature and brain parenchyma, and their relationship to observed decreases in cerebral blood flow as the disease progresses.},
	address = {San Francisco, California},
	booktitle = {Proceedings of the Joint Math Meeting 2010}
}
@article {
	title = {Studying the Role of ApoE in Alzheimer{\textquoteright}s Disease Pathogenesis Using a Systems Biology Model},
	author = {Kyrtsos, C Rose., Baras, John S.},
	year = {2013},
	month = {10/2013},
	abstract = {Alzheimer{\textquoteright}s disease (AD) is the most common form of dementia. Even with its well-known symptoms of memory loss and well-characterized pathology of beta-amyloid (Aβ) plaques and neurofibrillary tangles, the disease pathogenesis and initiating factors are still not well understood. To tackle this problem, a systems biology model has been developed and used to study the varying e{\textregistered}ects of variations in the ApoE allele present, as well as the e{\textregistered}ects of short term and periodic inflammation at low to moderate levels. Simulations showed a late onset peak of Aβ~in the ApoE4 case that lead to localized neuron loss which could be ameliorated in part by application of short-term pro-inflammatory mediators. The model that has been developed herein represents one of the first attempts to model AD from a systems approach to study physiologically relevant parameters that may prove useful to physicians in the future.},
	pages = {pp. 1342003.1-1342003.21},
	volume = {Vol. 11},
	number = {Issue 5},
	journal = {Journal of Bioinformatics and Computational Biology (JBCB)}
}
