Gold nanoparticle accumulation in immune cells has commonly been viewed as a side effect for cancer therapeutic delivery; however, this phenomenon can be utilized for developing gold nanoparticle mediated immunotherapy. Here, we conjugated a modified CpG oligodeoxynucleotide immune stimulant to gold nanoparticles using a simple and scalable self-assembled monolayer scheme that enhanced the functionality of CpG in vitro and in vivo. Nanoparticles can attenuate systemic side effects by enhancing CpG delivery passively to innate effector cells. The use of a triethylene glycol (TEG) spacer on top of the traditional poly-thymidine spacer increased CpG macrophage stimulatory effects without sacrificing DNA content on the nanoparticle, which directly correlates to particle uptake. In addition, the immune effects of modified CpG-AuNPs were altered by the core particle size, with smaller 15 nm AuNPs generating maximum immune response. These TEG modified CpG-AuNP complexes induced macrophage and dendritic cell tumor infiltration, significantly inhibited tumor growth, and promoted survival in mice when compared to treatments with free CpG.
Lithium metal plating on graphite anodes of Li-ion batteries is one of the causes of capacity fading and failure. An overcharge experiment on the graphite anode was conducted and the morphology and structure of graphite were characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). It was found that the failure mechanism of graphite during overcharge is similar to that of the lithium metal electrode. The deposited lithium will react with the electrolyte to form a new solid electrolyte interface (SEI) layer, which will prevent further accessibility during the following cycles. According to SEM and TEM images, this SEI layer shares the same morphologies of the lithium metal electrode during cycling.
This is the first study to document the clinical impact of frequent molecular monitoring, and the findings underscore the importance of regular molecular monitoring in delivering quality care for CML. These findings could be subject to unobserved confounders.
SDS reducing buffer was efficient at solubilizing proteins from stone matrix for further MS-based proteomic analysis. A variety of cellular, structural, and plasma proteins comprise COM stone matrix. Several of the stone proteins are involved in cell injury pathways, which suggests that inflammation plays a role in human COM stone formation.
Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid overfitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian matrix factorization algorithm using stochastic gradient MCMC. Our algorithm, based on Distributed Stochastic Gradient Langevin Dynamics, can not only match the prediction accuracy of standard MCMC methods like Gibbs sampling, but at the same time is as fast and simple as stochastic gradient descent. In our experiments, we show that our algorithm can achieve the same level of prediction accuracy as Gibbs sampling an order of magnitude faster. We also show that our method reduces the prediction error as fast as distributed stochastic gradient descent, achieving a 4.1% improvement in RMSE for the Netflix dataset and an 1.8% for the Yahoo music dataset.
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