A Design Methodology for Fault-Tolerant Neuromorphic Computing Using Bayesian Neural Network.

Memristor crossbar arrays are a promising platform for neuromorphic computing. In practical scenarios, the synapse weights represented by the memristors for the underlying system are subject to process variations, in which the programmed weight when read out for inference is no longer deterministic but a stochastic distribution. It is therefore highly desired to learn the weight distribution accounting for process variations, to ensure the same inference performance in memristor crossbar arrays as the design value. In this paper, we introduce a design methodology for fault-tolerant neuromorphic computing using a Bayesian neural network, which combines the variational Bayesian inference technique with a fault-aware variational posterior distribution. The proposed framework based on Bayesian inference incorporates the impacts of memristor deviations into algorithmic training, where the weight distributions of neural networks are optimized to accommodate uncertainties and minimize inference degradation. The experimental results confirm the capability of the proposed methodology to tolerate both process variations and noise, while achieving more robust computing in memristor crossbar arrays.

RNA sequencing profiles reveal dynamic signaling and glucose metabolic features during bone marrow mesenchymal stem cell senescence.

BACKGROUND: Stem cell senescence is considered as a significant driver of organismal aging. As individuals age, the number of stem cells is declined, and the ability to proliferate and survive is also weakened. It has been reported that metabolism plays an important role in stem cell self-renewal, multilineage differentiation, senescence and fate determination, which has aroused widespread concerns. However, whether metabolism-related genes or signalling pathways are involved in physiological aging remain largely undetermined. RESULTS: In the current study, we showed 868 up-regulated and 2006 down-regulated differentially expressed genes (DEGs) in bone marrow mesenchymal stem cells (MSCs) from old rats in comparison with that from young rats by performing RNA sequence. And DEGs functions and pathways were further selected by function enrichment analysis. The results indicated that the high expression of DEGs might participate in cell differentiation, growth factor binding and etc., while the down-regulated DEGs were majorly enriched in metabolism process, such as the cellular metabolic process and mitochondria. Then, we screened and verified DEGs related to glucose metabolism and investigated the glycolysis levels. We identified that glucose uptake, lactate secretion, ATP production and relative extracellular acidification rates (ECAR) were all diminished in MSCs from old rats. More importantly, we conducted microRNA prediction on the key DEGs of glycolysis to elucidate the potential molecular mechanisms of glucose metabolism affecting MSC senescence. CONCLUSIONS: Our study unravelled the profiles of DEGs in age-associated MSC senescence and their functions and pathways. We also clarified DEGs related to glucose metabolism and down-regulated glycolysis level in age-associated MSC senescence. This study will uncover the metabolic effects on regulating stem cell senescence, and provide novel therapeutic targets for ameliorating age-associated phenotypes.

Detection of aflatoxin B1 with a new label-free fluorescence aptasensor based on PVP-coated single-walled carbon nanohorns and SYBR Gold.

This paper describes a novel fluorescence label-free aptasensor to detect aflatoxin B1 (AFB1) by utilizing SYBR Gold, aptamer, and single-walled carbon nanohorns (SWCNHs). In the presence of AFB1, the conformation of AFB1-specific aptamer went through and the spatial structure of this specific aptamer was transformed accordingly. Due to the resistance of the transformed aptamer when adsorbed on the surface of SWCNHs, the protection of the fluorescence of SYBR Gold was accomplished. Consequently, concentrations of AFB1 showed a strong association with fluorescence intensity. The detection limit (LOD) of AFB1 was 1.89 ng/mL, while the linear range was 5-200 ng/mL and fluorescence intensity satisfactorily correlated (R2 = 0.9919) with the logarithm of AFB1 concentration.

What Happens When People with Depression Gather Online?

Depression is a common mental disease that impacts people of all ages and backgrounds. To meet needs that cannot otherwise be met, people with depression or who tend to suffer from depression often gather in online depression communities. However, since joining a depression community exposes members to the depression of others, the impact of such communities is not entirely clear. This study therefore explored what happens when people with depression gather in Sina Weibo's Depression Super Topic online community. Through website crawling, postings from Depression Super Topic were compared with postings from members' regular timelines with respect to themes, emotions disclosed, activity patterns, and the number of likes and comments. Topics of distilled postings covering support, regulations, emotions and life sharing, and initiating discussions were then coded. From comparison analysis, it was found that postings in the Depression Super Topic community received more comments and disclosed more emotions than regular timelines and that members were more active in the community at night. This study offers a picture of what occurs when people with depression gather online, which helps better understand their issues and therefore provide more targeted support.

Novel nanomicelles based on rebaudioside A: A potential nanoplatform for oral delivery of honokiol with enhanced oral bioavailability and antitumor activity.

Honokiol (HK) has a variety of biological activities, but its poor solubility limits its application. Rebaudioside A (RA) is able to self-assemble into micelles, which can be used for oral delivery of anticancer drugs. This study aims to create and evaluate a nano-sized anticancer drug delivery system based on RA, as RA micelles are thought to strengthen the therapeutic effects of HK. The results showed that RA and HK can be formulated into self-assembling micelles (RA-HK) with a size of 4.356 ± 0.142 nm and uniform distribution (PDI = 0.1906 ± 0.0184). Moreover, RA-HK could enhance the antitumor activity of HK in vitro. Further, it was shown that RA-HK can induce G0/G1 cycle arrest, apoptosis, and reactive oxygen species (ROS) generation in HuH-7 cells. The results for this mechanism indicate that RA-HK can induce DNA damage as well as changes in cycle and apoptotic-related proteins and activate the ERK signaling pathway. The in vivo antitumor results showed that RA-HK could also enhance the antitumor activity of HK in mice and does not induce any side effects. The pharmacokinetic results illustrate that RA-HK can increase the oral bioavailability of HK that and RA-HK is widely distributed in rats. Taken together, the above results prove that RA is a novel oral nano-drug delivery system with great potential for the delivery of hydrophobic antitumor drugs, such as HK.

Stable Tensor Principal Component Pursuit: Error Bounds and Efficient Algorithms.

The rapid development of sensor technology gives rise to the emergence of huge amounts of tensor (i.e., multi-dimensional array) data. For various reasons such as sensor failures and communication loss, the tensor data may be corrupted by not only small noises but also gross corruptions. This paper studies the Stable Tensor Principal Component Pursuit (STPCP) which aims to recover a tensor from its corrupted observations. Specifically, we propose a STPCP model based on the recently proposed tubal nuclear norm (TNN) which has shown superior performance in comparison with other tensor nuclear norms. Theoretically, we rigorously prove that under tensor incoherence conditions, the underlying tensor and the sparse corruption tensor can be stably recovered. Algorithmically, we first develop an ADMM algorithm and then accelerate it by designing a new algorithm based on orthogonal tensor factorization. The superiority and efficiency of the proposed algorithms is demonstrated through experiments on both synthetic and real data sets.

Partial characterization, in vitro antioxidant and antiproliferative activities of patatin purified from potato fruit juice.

Patatin from potato fruit juice was purified by a combination of ultrafiltration and chromatographic techniques. The in vitro antioxidant and antiproliferative activity against mouse melanoma B16 cells of patatin were investigated. The results showed that the monosaccharide composition of patatin included rhamnose, mannose, glucose, and galactose with a molar ratio of 41 : 30 : 21 : 8, and patatin consisted of (1 → 3) linked α-mannose, (1 → 4) linked α-galactose, (1 → 4) linked ß-glucose, and (1 → 2) linked α-rhamnose. Furthermore, patatin possessed significant antioxidant activities measured by scavenging of the DPPH and superoxide free radicals, notable reducing power, protective effects against hydroxyl radical-induced oxidative DNA damage and lipid peroxidation inhibitory. Moreover, patatin was identified as a potent antiproliferative agent against mouse melanoma B16 cells, causing cell cycle arrest in the G1 phase. Assays of apoptotic cells also showed that patatin treatment at concentrations of 20 mg mL(-1) resulted in a marked reduction of viable cells. These results obtained in in vitro models suggested that patatin may have potential application as a cancer chemopreventive agent and food ingredient.