Small interfering RNA (siRNA) enables efficient target gene silencing by employing a RNA interference (RNAi) mechanism, which can compromise gene expression and regulate gene activity by cleaving ...mRNA or repressing its translation. Twenty years after the discovery of RNAi in 1998, ONPATTRO™ (patisiran) (Alnylam Pharmaceuticals, Inc.), a lipid formulated siRNA modality, was approved for the first time by United States Food and Drug Administration and the European Commission in 2018. With this milestone achievement, siRNA therapeutics will soar in the coming years. Here, we review the discovery and the mechanisms of RNAi, briefly describe the delivery technologies of siRNA, and summarize recent clinical advances of siRNA therapeutics.
During software maintenance, developers spend a lot of time understanding the source code. Existing studies show that code comments help developers comprehend programs and reduce additional time ...spent on reading and navigating source code. Unfortunately, these comments are often mismatched, missing or outdated in software projects. Developers have to infer the functionality from the source code. This paper proposes a new approach named Hybrid-DeepCom to automatically generate code comments for the functional units of Java language, namely, Java methods. The generated comments aim to help developers understand the functionality of Java methods. Hybrid-DeepCom applies Natural Language Processing (NLP) techniques to learn from a large code corpus and generates comments from learned features. It formulates the comment generation task as the machine translation problem. Hybrid-DeepCom exploits a deep neural network that combines the lexical and structure information of Java methods for better comments generation. We conduct experiments on a large-scale Java corpus built from 9,714 open source projects on GitHub. We evaluate the experimental results on both machine translation metrics and information retrieval metrics. Experimental results demonstrate that our method Hybrid-DeepCom outperforms the state-of-the-art by a substantial margin. In addition, we evaluate the influence of out-of-vocabulary tokens on comment generation. The results show that reducing the out-of-vocabulary tokens improves the accuracy effectively.
This study empirically examines whether tourism affects poverty reduction based on the panel data of Chinese provinces for the period from 1999 to 2014. Using more comprehensive ...Foster–Greer–Thorbecke index to decompose poverty into three indices, namely, headcount ratio, poverty gap, and poverty severity, we investigate the relationship between tourism and poverty indices within a single framework. The empirical analysis indicates that tourism has a positive effect on poverty reduction and the concomitant inequality in the distribution of income among the poor could weaken the poverty reduction effect of tourism. China’s western provinces confirm a stronger relationship between tourism and poverty reduction, although the effect of tourism on poverty in the eastern provinces is nearly negligible. We also identify possible mechanisms by which tourism may have an impact on poverty. The results provide empirical evidence to provide an improved assessment of the pro-poor effect of tourism in China.
In the research of mining software repositories, we need to label a large amount of data to construct a predictive model. The correctness of the labels will affect the performance of a model ...substantially. However, limited studies have been performed to investigate the impact of mislabeled instances on a predictive model. To bridge the gap, in this article, we perform a case study on the security bug report (SBR) prediction. We found five publicly available datasets for SBR prediction contains many mislabeled instances, which lead to the poor performance of SBR prediction models of recent studies (e.g., the work of Peters et al. and Shu et al. ). Furthermore, it might mislead the research direction of SBR prediction. In this article, we first improve the label correctness of these five datasets by manually analyzing each bug report, and we find 749 SBRs, which are originally mislabeled as Non-SBRs (NSBRs). We then evaluate the impacts of datasets label correctness by comparing the performance of the classification models on both the noisy (i.e., before our correction) and the clean (i.e., after our correction) datasets. The results show that the cleaned datasets result in improvement in the performance of classification models. The performance of the approaches proposed by Peters et al. and Shu et al. on the clean datasets is much better than on the noisy datasets. Furthermore, with the clean datasets, the simple text classification models could significantly outperform the security keywords-matrix-based approaches applied by Peters et al. and Shu et al.
A randomized, parallel controlled, open-label clinical trial was conducted to evaluate the effect of a botanic compound berberine (BBR) on NAFLD.
A randomized, parallel controlled, open-label ...clinical trial was conducted in three medical centers (NIH Registration number: NCT00633282). A total of 184 eligible patients with NAFLD were enrolled and randomly received (i) lifestyle intervention (LSI), (ii) LSI plus pioglitazone (PGZ) 15mg qd, and (iii) LSI plus BBR 0.5g tid, respectively, for 16 weeks. Hepatic fat content (HFC), serum glucose and lipid profiles, liver enzymes and serum and urine BBR concentrations were assessed before and after treatment. We also analyzed hepatic BBR content and expression of genes related to glucose and lipid metabolism in an animal model of NAFLD treated with BBR.
As compared with LSI, BBR treatment plus LSI resulted in a significant reduction of HFC (52.7% vs 36.4%, p = 0.008), paralleled with better improvement in body weight, HOMA-IR, and serum lipid profiles (all p<0.05). BBR was more effective than PGZ 15mg qd in reducing body weight and improving lipid profile. BBR-related adverse events were mild and mainly occurred in digestive system. Serum and urine BBR concentrations were 6.99ng/ml and 79.2ng/ml, respectively, in the BBR-treated subjects. Animal experiments showed that BBR located favorably in the liver and altered hepatic metabolism-related gene expression.
BBR ameliorates NAFLD and related metabolic disorders. The therapeutic effect of BBR on NAFLD may involve a direct regulation of hepatic lipid metabolism.
ClinicalTrials.gov NCT00633282.
LncRNAs have been recognized as significant regulators in various diseases including neuropathic pain. Although the lncRNA NEAT1 has been reported to be involved in multiple cancers, its biological ...functions in neuropathic pain still remain unknown. In our present study, a chronic constriction injury (CCI) rat model was established and we found that NEAT1 was greatly upregulated in the spinal cord tissues of CCI rats. Knockdown of NEAT1 can repress neuropathic pain behaviors including mechanical and thermal hyperalgesia. In addition, NEAT1 downregulation inhibited neuroinflammation via inhibiting IL‐6, IL‐1β, and tumor necrosis factor (TNF)‐α in CCI rats. We also observed that miR‐381 was decreased significantly in CCI rats. By using bioinformatics analysis, miR‐381 was predicted to be a microRNA target of NEAT1, which indicated a negative correlation between miR‐381 and NEAT1. Inhibition of NEAT1 can induce miR‐381 expression in CCI rats, which indicated a negative correlation between NEAT1 and miR‐381. HMGB1, as a downstream target gene of miR‐381 was observed to be dramatically increased in CCI rats. miR‐381 can modulate HMGB1 expression negatively and meanwhile, NEAT1 was able to regulate HMGB1 through sponging miR‐381. Downregulation of HMGB1 can inhibit neuropathic pain behaviors which can be reversed by miR‐381 inhibitors. Taken these together, it was indicated that NEAT1 can induce neuropathic pain development in CCI rats via regulating miR‐381/HMGB1 axis.
We found that knockdown of NEAT1 can alleviate neuropathic pain by increasing miR‐381 and inhibiting neuro‐inflammation in CCI rats. For another, NEAT1 can modulate HMGB1 by sponging miR‐381 in neuropathic pain. Our findings indicated that NEAT1 can serve as a treatment target in neuropathic pain.
To quantitatively evaluate the output performance of triboelectric nanogenerators, figures of merit have been developed. However, the current figures of merit, without considering the breakdown ...effect that seriously affects the effective maximized energy output, are limited for application. Meanwhile, a method to evaluate output capability of nanogenerators is needed. Here, a standardized method that considers the breakdown effect is proposed for output capability assessment of nanogenerators. Contact separation and contact freestanding-triboelectric-layer modes triboelectric nanogenerators are used to demonstrate this method, and the effective maximized energy output and revised figures of merit are calculated based on the experimental results. These results are consistent with those theoretically calculated based on Paschen's law. This method is also conducted to evaluate a film-based piezoelectric nanogenerator, demonstrating its universal applicability for nanogenerators. This study proposes a standardized method for evaluating the effective output capability of nanogenerators, which is crucial for standardized evaluation and application of nanogenerator technologies.
Chemoresistance is a major unmet clinical obstacle in ovarian cancer treatment. Epigenetics plays a pivotal role in regulating the malignant phenotype, and has the potential in developing ...therapeutically valuable targets that improve the dismal outcome of this disease. Here we show that a series of transcription factors, including C/EBPβ, GCM1, and GATA1, could act as potential modulators of histone methylation in tumor cells. Of note, C/EBPβ, an independent prognostic factor for patients with ovarian cancer, mediates an important mechanism through which epigenetic enzyme modifies groups of functionally related genes in a context-dependent manner. By recruiting the methyltransferase DOT1L, C/EBPβ can maintain an open chromatin state by H3K79 methylation of multiple drug-resistance genes, thereby augmenting the chemoresistance of tumor cells. Therefore, we propose a new path against cancer epigenetics in which identifying and targeting the key regulators of epigenetics such as C/EBPβ may provide more precise therapeutic options in ovarian cancer.
Abstract
Triboelectric nanogenerators have attracted wide attention due to their promising capabilities of scavenging the ambient environmental mechanical energy. However, efficient energy management ...of the generated high-voltage for practical low-voltage applications is still under investigation. Autonomous switches are key elements for improving the harvested energy per mechanical cycle, but they are complicated to implement at such voltages higher than several hundreds of volts. This paper proposes a self-sustained and automatic hysteresis plasma switch made from silicon micromachining, and implemented in a two-stage efficient conditioning circuit for powering low-voltage devices using triboelectric nanogenerators. The hysteresis of this microelectromechanical switch is controllable by topological design and the actuation of the switch combines the principles of micro-discharge and electrostatic pulling, without the need of any power-consuming control electronic circuits. The experimental results indicate that the energy harvesting efficiency is improved by two orders of magnitude compared to the conventional full-wave rectifying circuit.
BP neural network is optimized by improved drosophila algorithm, and a prediction model for air quality in Nanchang is established based on the air quality data and meteorological data of Nanchang ...city in recent three years. The experimental results show that the improved algorithm has improved performance compared with the BP algorithm, and has improved accuracy 4%, with a small difference in time consumption. The performance of the indirect prediction method is slightly better than that of the direct prediction method
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