Advances in Treatment of Nocturnal Enuresis in Children

Nocturnal enuresis is a condition with complex etiology affecting plenty of children and families. Even though multifarious clinical trials and studies have been designed and completed, some inconclusive results on nocturnal enuresis confuse clinicians. This article aims to provide useful information for clinicians by summarizing the existing evidence on nocturnal enuresis and discussing the effectiveness and safety of different treatments. Nocturnal enuresis mainly results from the disorders related to central nervous system, which may cause nocturnal polyuria, nighttime bladder capacity decline, arousal disorder, and various accompanying diseases. We discussed the efficacy and safety of different treatments for monosymptomatic nocturnal enuresis, including standard therapies, simple behavioral interventions, complex behavioral interventions, alarm therapy, desmopressin and other drugs, biofeedback therapy, electrical stimulation, acupuncture, Chinese herbal medicine, massage, and so on. Alarm is still the most effective single therapy with lower relapse rate. Desmopressin has efficacy mainly in children with nocturnal polyuria. Children with detrusor overactivity or decreasing functional bladder capacity can choose anticholinergics. Additionally, tricyclic drugs, biofeedback therapy, electrical stimulation, acupuncture, massage, and so on are therapeutic options for children with nocturnal enuresis

Proof of User Similarity: the Spatial Measurer of Blockchain

Although proof of work (PoW) consensus dominates the current blockchain-based systems mostly, it has always been criticized for the uneconomic brute-force calculation. As alternatives, energy-conservation and energy-recycling mechanisms heaved in sight. In this paper, we propose proof of user similarity (PoUS), a distinct energy-recycling consensus mechanism, harnessing the valuable computing power to calculate the similarities of users, and enact the calculation results into the packing rule. However, the expensive calculation required in PoUS challenges miners in participating, and may induce plagiarism and lying risks. To resolve these issues, PoUS embraces the best-effort schema by allowing miners to compute partially. Besides, a voting mechanism based on the two-parties computation and Bayesian truth serum is proposed to guarantee privacy-preserved voting and truthful reports. Noticeably, PoUS distinguishes itself in recycling the computing power back to blockchain since it turns the resource wastage to facilitate refined cohort analysis of users, serving as the spatial measurer and enabling a searchable blockchain. We build a prototype of PoUS and compare its performance with PoW. The results show that PoUS outperforms PoW in achieving an average TPS improvement of 24.01% and an average confirmation latency reduction of 43.64%. Besides, PoUS functions well in mirroring the spatial information of users, with negligible computation time and communication cost.Comment: 12 pages,10 figure

Characterization of Electronic Cigarette Aerosol and Its Induction of Oxidative Stress Response in Oral Keratinocytes.

In this study, we have generated and characterized Electronic Cigarette (EC) aerosols using a combination of advanced technologies. In the gas phase, the particle number concentration (PNC) of EC aerosols was found to be positively correlated with puff duration whereas the PNC and size distribution may vary with different flavors and nicotine strength. In the liquid phase (water or cell culture media), the size of EC nanoparticles appeared to be significantly larger than those in the gas phase, which might be due to aggregation of nanoparticles in the liquid phase. By using in vitro high-throughput cytotoxicity assays, we have demonstrated that EC aerosols significantly decrease intracellular levels of glutathione in NHOKs in a dose-dependent fashion resulting in cytotoxicity. These findings suggest that EC aerosols cause cytotoxicity to oral epithelial cells in vitro, and the underlying molecular mechanisms may be or at least partially due to oxidative stress induced by toxic substances (e.g., nanoparticles and chemicals) present in EC aerosols

limma powers differential expression analyses for RNA-sequencing and microarray studies

limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously describe

The Role of CD1d and MR1 Restricted T Cells in the Liver

The liver is one of the most important immunological organs that remains tolerogenic in homeostasis yet promotes rapid responses to pathogens in the presence of a systemic infection. The composition of leucocytes in the liver is highly distinct from that of the blood and other lymphoid organs, particularly with respect to enrichment of innate T cells, i.e., invariant NKT cells (iNKT cells) and Mucosal-Associated Invariant T cells (MAIT cells). In recent years, studies have revealed insights into their biology and potential roles in maintaining the immune-environment in the liver. As the primary liver-resident immune cells, they are emerging as significant players in the human immune system and are associated with an increasing number of clinical diseases. As such, innate T cells are promising targets for modifying host defense and inflammation of various liver diseases, including viral, autoimmune, and those of tumor origin. In this review, we emphasize and discuss some of the recent discoveries and advances in the biology of innate T cells, their recruitment and diversity in the liver, and their role in various liver diseases, postulating on their potential application in immunotherapy

A Modified Bayesian Framework for Multi-Sensor Target Tracking with Out-of-Sequence-Measurements

Target detection and tracking is important in military as well as in civilian applications. In order to detect and track high-speed incoming threats, modern surveillance systems are equipped with multiple sensors to overcome the limitations of single-sensor based tracking systems. This research proposes the use of information from RADAR and Infrared sensors (IR) for tracking and estimating target state dynamics. A new technique is developed for information fusion of the two sensors in a way that enhances performance of the data association algorithm. The measurement acquisition and processing time of these sensors is not the same; consequently the fusion center measurements arrive out of sequence. To ensure the practicality of system, proposed algorithm compensates the Out of Sequence Measurements (OOSMs) in cluttered environment. This is achieved by a novel algorithm which incorporates a retrodiction based approach to compensate the effects of OOSMs in a modified Bayesian technique. The proposed modification includes a new gating strategy to fuse and select measurements from two sensors which originate from the same target. The state estimation performance is evaluated in terms of Root Mean Squared Error (RMSE) for both position and velocity, whereas, track retention statistics are evaluated to gauge the performance of the proposed tracking algorithm. The results clearly show that the proposed technique improves track retention and and false track discrimination (FTD)

A two-step lineage reprogramming strategy to generate functionally competent human hepatocytes from fibroblasts

Terminally differentiated cells can be generated by lineage reprogramming, which is, however, hindered by incomplete conversion with residual initial cell identity and partial functionality. Here, we demonstrate a new reprogramming strategy by mimicking the natural regeneration route, which permits generating expandable hepatic progenitor cells and functionally competent human hepatocytes. Fibroblasts were first induced into human hepatic progenitor-like cells (hHPLCs), which could robustly expand in vitro and efficiently engraft in vivo. Moreover, hHPLCs could be efficiently induced into mature human hepatocytes (hiHeps) in vitro, whose molecular identity highly resembles primary human hepatocytes (PHHs). Most importantly, hiHeps could be generated in large quantity and were functionally competent to replace PHHs for drug-metabolism estimation, toxicity prediction and hepatitis B virus infection modeling. Our results highlight the advantages of the progenitor stage for successful lineage reprogramming. This strategy is promising for generating other mature human cell types by lineage reprogramming.</p