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The development of two different immunoassays for the determination of fumonisin B1 in wheat samples is reported. A previously described mimopeptide for fumonisin B1 (FB1) was used to produce fusion proteins in combination with two different luciferases: Gaussia luciferase (GLuc) and NanoLuc luciferase (NLuc). The production, expression and the development of two immunoassays based on these fusion proteins (A2- GLuc and A2-NLuc) is detailed. The assay showing the best performance, A2-NLuc, with a limit of detection of 0.61 ngmL 1 and a dynamic range from 1.9 to 95 ngmL 1 , was employed for the analysis of spiked wheat samples, a reference matrix material, as well as naturally contaminated wheat samples. The recoveries obtained in the spiked samples were acceptable, between 81.5 and 109%, with relative standard deviations lower than 14%. The analysis of naturally contaminated wheat was validated by a liquid chromatography coupled to tandem mass detection method.

Typical protein biosensors employ chemical or genetic labeling of the protein, thus introducing an extraneous molecule to the wild-type parent protein, often changing the overall structure and properties of the protein. While these labeling methods have proven successful in many cases, they also have a series of disadvantages associated with their preparation and function. An alternative route for labeling proteins is the incorporation of unnatural amino acid (UAA) analogues, capable of acting as a label, into the structure of a protein. Such an approach, while changing the local microenvironment, poses less of a burden on the overall structure of the protein. L-DOPA is an analog of phenylalanine and contains a catechol moiety that participates in a quasi-reversible, two-electron redox process, thus making it suitable as an electrochemical label/reporter. The periplasmic glucose/galactose binding protein (GBP) was chosen to demonstrate this detection principle. Upon glucose binding, GBP undergoes a significant conformational change that is manifested as a change in the electrochemistry of L-DOPA. The electroactive GBP was immobilized onto gold nanoparticle-modified, polymerized caffeic acid, screen-printed carbon electrodes (GBP-LDOPA/AuNP/PCA/SPCE) for the purpose of direct measurement of glucose levels and serves as a proof-of-concept of the use of electrochemically-active unnatural amino acids as the label. The resulting reagentless GBP biosensors exhibited a highly selective and sensitive binding affinity for glucose in the micromolar range, laying the foundation for a new biosensing methodology based on global incorporation of an electroactive amino acid into the protein's primary sequence for highly selective electrochemical detection of compounds of interest.

A considerable volume of research over the last decade has focused on understanding the fundamental mechanisms for the progression of atherosclerosis-the underlying cause for the vast majority of all cardiovascular (CVD)-related complications. Aging is the dominant risk factor for clinically significant atherosclerotic lesion formation, yet the heightened impact of aging on the disease is not accounted for by changes in traditional risk factors, such as lack of physical activity, smoking, hypertension, hyperlipidemia, or diabetes mellitus. This review will examine the pathological and biochemical processes of atherosclerotic plaque formation and growth, with particular focus on the aging risk vis-a-vis arterial homeostasis. Particular focus will be placed on the impact of a number of important contributors to arterial homeostasis including bone marrow (BM)-derived vascular progenitor cells, differential monocyte subpopulations, and the role of cellular senescence. Finally, this review will explore many critical observations in the way the disease process has been reassessed both by clinicians and researchers, and will highlight recent advances in this field that have provided a greater understanding of this aging-driven disease.

Sudden Cardiac Death (SCD) is responsible for at least 180,000 deaths a year and incurs an average cost of $286 billion annually in the United States alone. Herein, we present a novel discrete event simulation model of SCD, which quantifies the chains of events associated with the formation, growth, and rupture of atheroma plaques, and the subsequent formation of clots, thrombosis and on-set of arrhythmias within a population. The predictions generated by the model are in good agreement both with results obtained from pathological examinations on the frequencies of three major types of atheroma, and with epidemiological data on the prevalence and risk of SCD. These model predictions allow for identification of interventions and importantly for the optimal time of intervention leading to high potential impact on SCD risk reduction (up to 8-fold reduction in the number of SCDs in the population) as well as the increase in life expectancy.