Publications by authors named "Joan T Matamalas"

The coronavirus disease (COVID-19) pandemic has occurred in Massachusetts in multiple waves led by a series of emerging variants. While the evidence has linked obesity with severe symptoms of COVID-19, the effect of obesity on susceptibility to SARS-CoV-2 infection remains unclear. Identification of intrinsic factors, which increase the likelihood of exposed individuals succumbing to productive SARS-CoV-2 infection could help plan mitigation efforts to curb the illness.

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Background: Interferon-γ (IFNγ) signaling plays a complex role in atherogenesis. IFNγ stimulation of macrophages permits in vitro exploration of proinflammatory mechanisms and the development of novel immune therapies. We hypothesized that the study of macrophage subpopulations could lead to anti-inflammatory interventions.

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Cellular heterogeneity of aortic valves complicates the mechanistic evaluation of the calcification processes in calcific aortic valve disease (CAVD), and animal disease models are lacking. In this study, we identify a disease-driver population (DDP) within valvular interstitial cells (VICs). Through stepwise single-cell analysis, phenotype-guided omic profiling, and network-based analysis, we characterize the DDP fingerprint as CD44CD29CD59CD73CD45 and discover potential key regulators of human CAVD.

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Background: Vein graft failure remains a common clinical challenge. We applied a systems approach in mouse experiments to discover therapeutic targets for vein graft failure.

Methods: Global proteomics and high-dimensional clustering on multiple vein graft tissues were used to identify potential pathogenic mechanisms.

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Many real systems are strongly characterized by collective cooperative phenomena whose existence and properties still need a satisfactory explanation. Coherently with their collective nature, they call for new and more accurate descriptions going beyond pairwise models, such as graphs, in which all the interactions are considered as involving only two individuals at a time. Hypergraphs respond to this need, providing a mathematical representation of a system allowing from pairs to larger groups.

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Epidemic containment is a major concern when confronting large-scale infections in complex networks. Many studies have been devoted to analytically understand how to restructure the network to minimize the impact of major outbreaks of infections at large scale. In many cases, the strategies are based on isolating certain nodes, while less attention has been paid to interventions on the links.

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Understanding how people move within a geographical area, e.g. a city, a country or the whole world, is fundamental in several applications, from predicting the spatio-temporal evolution of an epidemic to inferring migration patterns.

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Cooperation is a very common, yet not fully-understood phenomenon in natural and human systems. The introduction of a network within the population is known to affect the outcome of cooperative dynamics, allowing for the survival of cooperation in adverse scenarios. Recently, the introduction of multiplex networks has yet again modified the expectations for the outcome of the Prisoner's Dilemma game, compared to the monoplex case.

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