Multispectral nanoparticle tracking analysis for the real-time characterization of amyloid-β self assembly in vitro (Conference Presentation)

Author(s):  
Colman Moore ◽  
Ryan Wing ◽  
Jesse V. Jokerst
PLoS ONE ◽  
2019 ◽  
Vol 14 (7) ◽  
pp. e0219465 ◽  
Author(s):  
Miki Eto ◽  
Tadafumi Hashimoto ◽  
Takao Shimizu ◽  
Takeshi Iwatsubo

Inorganics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 91 ◽  
Author(s):  
Marta Gozzi ◽  
Benedikt Schwarze ◽  
Peter Coburger ◽  
Evamarie Hey-Hawkins

3,1,2-Ruthenadicarbadodecaborane complexes bearing the [C2B9H11]2− (dicarbollide) ligand are robust scaffolds, with exceptional thermal and chemical stability. Our previous work has shown that these complexes possess promising anti-tumor activities in vitro, and tend to form aggregates (or self-assemblies) in aqueous solutions. Here, we report on the synthesis and characterization of four ruthenium(II) complexes of the type [3-(η6-arene)-1,2-R2-3,1,2-RuC2B9H9], bearing either non-polar (R = Me (2–4)) or polar (R = CO2Me (7)) substituents at the cluster carbon atoms. The behavior in aqueous solution of complexes 2, 7 and the parent unsubstituted [3-(η6-p-cymene)-3,1,2-RuC2B9H11] (8) was investigated via UV-Vis spectroscopy, mass spectrometry and nanoparticle tracking analysis (NTA). All complexes showed spontaneous formation of self-assemblies (108–109 particles mL−1), at low micromolar concentration, with high polydispersity. For perspective applications in medicine, there is thus a strong need for further characterization of the spontaneous self-assembly behavior in aqueous solutions for the class of neutral metallacarboranes, with the ultimate scope of finding the optimal conditions for exploiting this self-assembling behavior for improved biological performance.


1984 ◽  
Vol 106 (1) ◽  
pp. 83-88 ◽  
Author(s):  
T. Kitamura ◽  
T. Kijima ◽  
H. Akashi

This paper demonstrates a modeling technique of prosthetic heart valves. In the modeling, a pumping cycle is divided into four phases, in which the state of the valve and flow is different. The pressure-flow relation across the valve is formulated separately in each phase. This technique is developed to build a mathematical model used in the real time estimation of the hemodynamic state under artificial heart pumping. The model built by this technique is simple enough for saving the computational time in the real time estimation. The model is described by the first-order ordinary differential equation with 12 parameters. These parameters can be uniquely determined beforehand from in-vitro experimental data. It is shown that the model can adapt, with sufficient accuracy, to a change in the practical pumping condition and the viscosity of the fluid in their practical range, and is also demonstrated that the estimated backflow volume by model agrees closely with the actual one.


2019 ◽  
Author(s):  
Siddhartha Banerjee ◽  
Mohtadin Hashemi ◽  
Karen Zagorski ◽  
Yuri L. Lyubchenko

AbstractThe assembly of polypeptides and proteins into nanoscale aggregates is a phenomenon observed in a vast majority of proteins. Importantly, aggregation of amyloid β (Aβ) proteins is considered as a major cause for the development of Alzheimer’s disease. The process depends on various conditions and typical test-tube experiments require high protein concentration that complicates the translation of results obtained in vitro to understanding the aggregation process in vivo. Here we demonstrate that Aβ42 monomers at the membrane bilayer are capable of self-assembling into aggregates at physiologically low concentrations, and the membrane in this aggregation process plays a role of a catalyst. We applied all-atom molecular dynamics to demonstrate that the interaction with the membrane surface dramatically changes the conformation of Aβ42 protein. As a result, the misfolded Aβ42 rapidly assembles into dimers, trimers and tetramers, so the on-surface aggregation is the mechanism by which amyloid oligomers are produced and spread.


2020 ◽  
Vol 7 (24) ◽  
pp. 2070137
Author(s):  
Hyunjin Kim ◽  
Hee Yeon Kim ◽  
Eun Young Lee ◽  
Boem Kyu Choi ◽  
Hyonchol Jang ◽  
...  

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