Publications by authors named "K Magor"

Prediction of outcomes following a prenatal diagnosis of congenital heart disease (CHD) is challenging. Machine learning (ML) algorithms may be used to reduce clinical uncertainty and improve prognostic accuracy. We performed a pilot study to train ML algorithms to predict postnatal outcomes based on clinical data.

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Deterioration of physiological systems, like the cardiovascular system, occurs progressively with age impacting an individual's health and increasing susceptibility to injury and disease. Cellular senescence has an underlying role in age-related alterations and can be triggered by natural aging or prematurely by stressors such as the bacterial toxin lipopolysaccharide (LPS). The metabolism of polyunsaturated fatty acids by CYP450 enzymes produces numerous bioactive lipid mediators that can be further metabolized by soluble epoxide hydrolase (sEH) into diol metabolites, often with reduced biological effects.

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Tripartite motif (TRIM) proteins are involved in development, innate immunity, and viral restriction. TRIM gene repertoires vary between species, likely due to diversification caused by selective pressures from pathogens; however, this has not been explored in birds. We mined a assembled transcriptome for the TRIM gene repertoire of the domestic mallard duck (), a reservoir host of influenza A viruses.

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The nonstructural protein 1 (NS1) of influenza A viruses is an important virulence factor that controls host cell immune responses. In human cells, NS1 proteins inhibit the induction of type I interferon by several mechanisms, including potentially, by preventing the activation of the retinoic acid-inducible gene I (RIG-I) receptor by the ubiquitin ligase tripartite motif-containing protein 25 (TRIM25). It is unclear whether the inhibition of human TRIM25 is a universal function of all influenza A NS1 proteins or is strain dependent.

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Animal species differ considerably in their ability to fight off infections. Finding the genetic basis of these differences is not easy, as the immune response is comprised of a complex network of proteins that interact with one another to defend the body against infection. Here, we used population- and comparative genomics to study the evolutionary forces acting on the innate immune system in natural hosts of the avian influenza virus (AIV).

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