Hybrid Biodegradable Nanomotors through Compartmentalized Synthesis

Designer particles that are embued with nanomachinery for autonomous motion have great potential for biomedical applications; however, their development is highly demanding with respect to biodegradability/compatibility. Previously, biodegradable propulsive machinery based on enzymes has been presented. However, enzymes are highly susceptible to proteolysis and deactivation in biological milieu. Biodegradable hybrid nanomotors powered by catalytic inorganic nanoparticles provide a proteolytically stable alternative to those based upon enzymes. Herein we describe the assembly of hybrid biodegradable nanomotors capable of transducing chemical energy into motion. Such nanomotors are constructed through a process of compartmentalized synthesis of inorganic MnO2 nanoparticles (MnPs) within the cavity of organic stomatocytes. We show that the nanomotors remain active in cellular environments and do not compromise cell viability. Effective tumor penetration of hybrid nanomotors is also demonstrated in proof-of-principle experiments. Overall, this work represents a new prospect for engineering of nanomotors that can retain their functionality within biological contexts

Engineering transient dynamics of artificial cells by stochastic distribution of enzymes

Here the authors develop a coacervate micromotor that can display autonomous motion as a result of stochastic distribution of propelling units. This stochastic-induced mobility is validated and explained through experiments and theory. Random fluctuations are inherent to all complex molecular systems. Although nature has evolved mechanisms to control stochastic events to achieve the desired biological output, reproducing this in synthetic systems represents a significant challenge. Here we present an artificial platform that enables us to exploit stochasticity to direct motile behavior. We found that enzymes, when confined to the fluidic polymer membrane of a core-shell coacervate, were distributed stochastically in time and space. This resulted in a transient, asymmetric configuration of propulsive units, which imparted motility to such coacervates in presence of substrate. This mechanism was confirmed by stochastic modelling and simulations in silico. Furthermore, we showed that a deeper understanding of the mechanism of stochasticity could be utilized to modulate the motion output. Conceptually, this work represents a leap in design philosophy in the construction of synthetic systems with life-like behaviors

Salmon Calcitonin Exerts an Antidepressant Effect by Activating Amylin Receptors

Depressive disorder is defined as a psychiatric disease characterized by the core symptoms of anhedonia and learned helplessness. Currently, the treatment of depression still calls for medications with high effectiveness, rapid action, and few side effects, although many drugs, including fluoxetine and ketamine, have been approved for clinical usage by the Food and Drug Administration (FDA). In this study, we focused on calcitonin as an amylin receptor polypeptide, of which the antidepressant effect has not been reported, even if calcitonin gene-related peptides have been previously demonstrated to improve depressive-like behaviors in rodents. Here, the antidepressant potential of salmon calcitonin (sCT) was first evaluated in a chronic restraint stress (CRS) mouse model of depression. We observed that the immobility duration in CRS mice was significantly increased during the tail suspension test and forced swimming test. Furthermore, a single administration of sCT was found to successfully rescue depressive-like behaviors in CRS mice. Lastly, AC187 as a potent amylin receptor antagonist was applied to investigate the roles of amylin receptors in depression. We found that AC187 significantly eliminated the antidepressant effects of sCT. Taken together, our data revealed that sCT could ameliorate a depressive-like phenotype probably via the amylin signaling pathway. sCT should be considered as a potential therapeutic candidate for depressive disorder in the future

Atomic library optimization for pulse ultrasonic sparse signal decomposition and reconstruction

Compressive sampling of pulse ultrasonic NDE signals could bring significant savings in the data acquisition process. Sparse representation of these signals using an atomic library is key to their interpretation and reconstruction from compressive samples. However, the obstacles to practical applicability of such representations are: large size of the atomic library and computational complexity of the sparse decomposition and reconstruction. To help solve these problems, we develop a method for optimizing the ranges of parameters of traditional Gabor-atom library to match a real pulse ultrasonic signal in terms of correlation. As a result of atomic-library optimization, the number of the atoms is greatly reduced. Numerical simulations compare the proposed approach with the traditional method. Simulation results show that both the time efficiency and signal reconstruction energy error are superior to the traditional one even with small-scale atomic library. The performance of the proposed method is also explored under different noise levels. Finally, we apply the proposed method to real pipeline ultrasonic testing data, and the results indicate that our reduced atomic library outperforms the traditional library.This proceeding may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This proceeding appeared in Song, Shoupeng, Yingxue Li, and Aleksandar Dogandžić. "Atomic library optimization for pulse ultrasonic sparse signal decomposition and reconstruction." In AIP Conference Proceedings, vol. 1706, no. 1, p. 180008. AIP Publishing LLC, 2016, and may be found at DOI: 10.1063/1.4940638. Copyright 2016 AIP Publishing LLC. Posted with permission

Atomic library optimization for pulse ultrasonic sparse signal decomposition and reconstruction

Compressive sampling of pulse ultrasonic NDE signals could bring significant savings in the data acquisition process. Sparse representation of these signals using an atomic library is key to their interpretation and reconstruction from compressive samples. However, the obstacles to practical applicability of such representations are: large size of the atomic library and computational complexity of the sparse decomposition and reconstruction. To help solve these problems, we develop a method for optimizing the ranges of parameters of traditional Gabor-atom library to match a real pulse ultrasonic signal in terms of correlation. As a result of atomic-library optimization, the number of the atoms is greatly reduced. Numerical simulations compare the proposed approach with the traditional method. Simulation results show that both the time efficiency and signal reconstruction energy error are superior to the traditional one even with small-scale atomic library. The performance of the proposed method is also explored under different noise levels. Finally, we apply the proposed method to real pipeline ultrasonic testing data, and the results indicate that our reduced atomic library outperforms the traditional library.This proceeding may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This proceeding appeared in Song, Shoupeng, Yingxue Li, and Aleksandar Dogandžić. "Atomic library optimization for pulse ultrasonic sparse signal decomposition and reconstruction." In AIP Conference Proceedings, vol. 1706, no. 1, p. 180008. AIP Publishing LLC, 2016, and may be found at DOI: 10.1063/1.4940638. Copyright 2016 AIP Publishing LLC. Posted with permission

Causal association of calcific aortic valve stenosis and atrial fibrillation: a Mendelian randomization study

Abstract Calcific aortic valve stenosis (CAVS) is associated with an increased risk of atrial fibrillation (AF) in observational studies, but whether these associations are causal has not been determined. This study aimed to explore the potential causal relationship between CAVS and AF via Mendelian randomization (MR). Genetic variants from the genome-wide association study (GWAS) summary data of the European population for CAVS were used to investigate the association with AF. The inverse variance weighted (IVW) approach was used to obtain the primary causal inference, and several sensitivity analysis approaches, such as the MR‒Egger and weighted median (WM), were performed to assess the robustness of the results. A total of nineteen valid and independent genetic SNPs associated with CAVS were obtained from the GWAS database. Genetically predicted CAVS (OR: 1.105; 95% CI: 1.072–1.139; p = 8.60E−11) was associated with an increased risk of AF. Similar results were discovered in the sensitivity analyses by using MR Egger and weighted median approaches. An MR design was used to reduce confounding variables and the potential for reverse causality bias. The results provide genetic evidence that CAVS considerably increased the risk of AF

Optimization of 3D Surfaces of Dextran with Different Molecule Weights for Real-Time Detection of Biomolecular Interactions by a QCM Biosensor

Quartz crystal microbalance (QCM) has been extensively applied in real-time and label-free biomolecular interaction studies. However, the sensitive detection by QCM technology remains challenging, mainly due to the limited surface immobilization capacity. Here, a three-dimensional (3D) carboxymethyl dextran coated gold sensor chip surface was successfully fabricated with dextran of different molecular weight (100, 500 and 2000 kDa, respectively). To evaluate the 3D carboxymethyl dextran surface immobilization capacity, the 3D surface was used for studying antigen–antibody interactions on the QCM biosensor. The results showed that the protein immobilization capacity of the 3D carboxymethyl dextran (2000 kDa) surface exceeded more than 4 times the capacity of the 2D carboxyl surface, and 2 times the capacity of the traditional 3D carboxymethyl dextran (500 kDa) surface. Furthermore, the kinetic and affinity properties of antigen–antibody interactions were performed. Most notably, the optimized 3D carboxymethyl dextran (2000 kDa) surface could be used for small molecule detection, where the binding of biotinylated oligo (0.67 kDa) reached 8.1 Hz. The results confirmed that a 3D carboxymethyl dextran (2000 kDa) surface can be exploited for sensitive detection of low molecular weight analytes, which have great potential applications for characterizing the interactions between small molecule drugs and proteins

ATP-mediated transient behavior of stomatocyte nanosystems

In nature, dynamic processes are ubiquitous and often characterized by adaptive, transient behavior. Herein, we present the development of a transient bowl-shaped nanoreactor system, or stomatocyte, the properties of which are mediated by molecular interactions. In a stepwise fashion, we couple motility to a dynamic process, which is maintained by transient events; namely, binding and unbinding of adenosine triphosphate (ATP). The surface of the nanosystem is decorated with polylysine (PLL), and regulation is achieved by addition of ATP. The dynamic interaction between PLL and ATP leads to an increase in the hydrophobicity of the PLL–ATP complex and subsequently to a collapse of the polymer; this causes a narrowing of the opening of the stomatocytes. The presence of the apyrase, which hydrolyzes ATP, leads to a decrease of the ATP concentration, decomplexation of PLL, and reopening of the stomatocyte. The competition between ATP input and consumption gives rise to a transient state that is controlled by the out-of-equilibrium process