The Role of Initial Oligomers in Amyloid Fibril Formation by Human Stefin B

Oligomers are commonly observed intermediates at the initial stages of amyloid fibril formation. They are toxic to neurons and cause decrease in neural transmission and long-term potentiation. We describe an in vitro study of the initial steps in amyloid fibril formation by human stefin B, which proved to be a good model system. Due to relative stability of the initial oligomers of stefin B, electrospray ionization mass spectrometry (ESI MS) could be applied in addition to size exclusion chromatography (SEC). These two techniques enabled us to separate and detect distinguished oligomers from the monomers: dimers, trimers, tetramers, up to decamers. The amyloid fibril formation process was followed at different pH and temperatures, including such conditions where the process was slow enough to detect the initial oligomeric species at the very beginning of the lag phase and those at the end of the lag phase. Taking into account the results of the lower-order oligomers transformations early in the process, we were able to propose an improved model for the stefin B fibril formation.     

Nitro-Oleic Acid Reduces J774A.1 Macrophage Oxidative Status and Triglyceride Mass: Involvement of Paraoxonase2 and Triglyceride Metabolizing Enzymes

Nitro‐fatty acids possess anti‐atherogenic properties, but their effects on macrophage oxidative status and lipid metabolism that play important roles in atherosclerosis development are unclear. This study compared the effects of nitro‐oleic acid (OLA‐NO₂) with those of native oleic acid (OLA) on intracellular reactive oxygen species (ROS) generation, anti‐oxidants and metabolism of triglycerides and cholesterol in J774A.1 macrophages. Upon incubating the cells with physiological concentrations of OLA‐NO₂ (0–1 µM) or with equivalent levels of OLA, ROS levels measured by 2, 7‐dichlorofluorescein diacetate, decreased dose‐dependently, but the anti‐oxidative effects of OLA‐NO₂ were significantly augmented. Copper ion addition increased ROS generation in OLA treated macrophages without affecting OLA‐NO₂ treated cells. These effects could be attributed to elevated glutathione levels and to increased activity and expression of paraoxonase2 that were observed in OLA‐NO₂vs OLA treated cells. Beneficial effects on triglyceride metabolism were noted in OLA‐NO₂vs OLA treated macrophages in which cellular triglycerides were reduced due to attenuated biosynthesis and accelerated hydrolysis of triglycerides. Accordingly, OLA‐NO₂ treated cells demonstrated down‐regulation of diacylglycerol acyltransferase1, the key enzyme in triglyceride biosynthesis, and increased expression of hormone‐sensitive lipase and adipose triglyceride lipase that regulate triglyceride hydrolysis. Finally, OLA‐NO₂vs OLA treatment resulted in modest but significant beneficial effects on macrophage cholesterol metabolism, reducing cholesterol biosynthesis rate and low density lipoprotein influx into the cells, while increasing high density lipoprotein‐mediated cholesterol efflux from the macrophages. Collectively, compared with OLA, OLA‐NO₂ modestly but significantly reduces macrophage oxidative status and cellular triglyceride content via modulation of cellular anti‐oxidants and triglyceride metabolizing enzymes.     

Random environment integer‐valued autoregressive process

An r states random environment integer‐valued autoregressive process of order 1, RrINAR(1), is introduced. Also, a random environment process is separately defined as a selection mechanism of differently parameterized geometric distributions, thus ensuring the non‐stationary nature of the RrNGINAR(1) model based on the negative binomial thinning. The distributional and correlation properties of this model are discussed, and the k‐step‐ahead conditional expectation and variance are derived. Yule–Walker estimators of model parameters are presented and their strong consistency is proved. The RrNGINAR(1) model motivation is justified on simulated samples and by its application to specific real‐life counting data.