Bacteria from nodules of Abrus mollis Hance: genetic diversity and screening of highly efficient growth-promoting strains

IntroductionAbrus mollis Hance. (AM) is an important species used in southern Chinese medicine. It is mainly found in Guangdong and Guangxi provinces in China, and it is effective in the treatment of hepatitis. Endophytic bacteria are known to affect the growth and quality of medicinal plants. However, there are limited reports describing endophytic bacteria related to AM.MethodsIn the present study, Illumina-based 16S rRNA gene sequencing was used to investigate the endophytic bacterial communities of root nodules of AM at five sampling sites in Guangxi. In addition, 179 strains of endophytic bacteria were isolated and categorized into 13 haplotypes based on recA sequence analysis.ResultsThe phylogeny of the 16S rRNA gene sequences revealed a predominance of nonrhizobial endophytes. Microbial diversity analysis showed that Proteobacteria was the dominant phylum in all samples, while Bradyrhizobium was the dominant genus in different samples. An efficient strain, Rhizobium tropici FM-19, was screened and obtained through greenhouse experiments. The AM plants inoculated with this strain showed the best growth performance and high nitrogen fixation and nodulation capacity. Notably, total phenols and total flavonoids, important active components in AM, increased by 30.9 and 42.7%, respectively, after inoculation with Rhizobium tropici FM-19.DiscussionThis study provides insights into the complex microbial diversity of AM nodules and provides strain information for the efficient cultivation of AM

Effects of the Zishen Yutai Pill compared with placebo on pregnancy outcomes among women in a fresh embryo transfer cycle: a Post Hoc subgroup analysis of a randomized controlled trial

ObjectiveTo assess whether the administration of Zishen Yutai Pill (ZYP) could improve the pregnancy outcomes in different subgroups of women undergoing fresh embryo transfer cycles.Materials and methodsThis is a post hoc analysis of a large scale, placebo-controlled, double blind, randomized clinical trial (RCT) regarding the use of ZYP during assisted reproductive technology (ART) treatment. The RCT was conducted at 19 in vitro fertilization (IVF) centers between April 2014 and June 2017. A total of 2265 women undergoing fresh embryo transfer cycles were randomly assigned in a 1:1 ratio to receive ZYP (n = 1131) or placebo (n = 1134). Post hoc logistic regression analyses were applied in this study to examine the between-group differences of ZYP and placebo on clinical pregnancy rate among different subgroups. Detailed analyses, both in intention-to-treat (ITT) and per-protocol population, were also conducted in specific subgroups with regards to rates of implantation, biochemical pregnancy, clinical pregnancy, live birth, pregnancy loss, as well as other neonatal indices.ResultsZYP showed a significantly higher clinical pregnancy rates than placebo in the ITT population. Detailed subgroup analyses were conducted in subgroup in advanced maternal age (AMA, ≥ 35 years old) and overweight/obese patients (BMI > 24), due to the clinical importance and statistical results. In these subgroups, baseline characteristics were similar between two arms (all P > 0.05). Significantly elevated clinical pregnancy rates were observed in ZYP cohort (both P < 0.05) compared with the placebo group. Results also showed that ZYP treatment resulted in significantly higher rates of implantation, biochemical pregnancy in AMA or overweight/obese patients in ITT analysis (all P < 0.05).ConclusionsThe current post hoc subgroup analysis suggested that AMA and overweight/obese women could experience clinical benefits when treated with ZYP in their fresh embryo transfer cycles. The study provides references for the use of ZYP in ART practices. However, further studies in specific subgroups should be examined in more rigorous clinical trial settings.Clinical trial registrationChictr.org.cn, ChictrTRC-14004494

Gremlin1 Delivered by Mesenchymal Stromal Cells Promoted Epithelial-Mesenchymal Transition in Human Esophageal Squamous Cell Carcinoma

Backgroud/Aims: Mesenchymal stromal cells (MSCs) are a major component of the tumor microenvironment (TME). Several studies focusing on tumor-derived MSCs have demonstrated that they exhibit a strong ability to promote the tumor epithelial-mesenchymal transition (EMT). However, the factors mediating these effects are poorly understood. Methods: Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and immunohistochemistry assays were used to detect the expression of Gremlin1 (GREM1) in human esophageal squamous cell carcinoma (ESCC) tissues. ShRNA silencing, flow cytometry, cell counting kit (CCK8) assay, invasion assay, western blot were used to detect the effect of GREM1 in ECa109, TE-1 cell lines and xenograft tumor models. Results: In the current study, we found that the GREM1 was overexpressed in human ESCC tissues. The conditioned medium from mesenchymal stromal cells (MSCs-CM) enhanced the malignancy of xenograft esophageal tumors in vivo, as well as the cell proliferation, viability and invasion of the esophageal carcinoma cell lines ECa109 and TE-1 in vitro. Furthermore, the shRNA silencing of GREM1 in MSCs (shGREM1-MSCs) reversed the increased malignancy of the esophageal tumor in vivo, while the conditioned medium from shGREM1-MSCs (shGREM1-MSCs-CM) affected the cell cycle and cell invasion in vitro. These processes were accompanied by the EMT in the ECa109 and TE-1 cell lines with an alteration in the expression levels of mesenchymal and epithelial markers. Furthermore, the TGF-β/BMP (transforming growth factor-beta/bone morphogenetic protein) signaling pathway participated in the shGREM1-MSCs-CM-induced anti-tumor effect on enhanced esophageal malignancy induced by MSCs-CM treatment. Conclusions: Taken together, our study suggested that GREM1 delivered by MSCs promoted EMT in ESCC in vitro and in vivo, which is partly through TGF-β/BMP signaling pathway. The results provide experimental evidence to a potential therapeutic target in the treatment of esophageal cancer

17β-Estradiol Enhances Breast Cancer Cell Motility and Invasion via Extra-Nuclear Activation of Actin-Binding Protein Ezrin

Estrogen promotes breast cancer metastasis. However, the detailed mechanism remains largely unknown. The actin binding protein ezrin is a key component in tumor metastasis and its over-expression is positively correlated to the poor outcome of breast cancer. In this study, we investigate the effects of 17β-estradiol (E2) on the activation of ezrin and its role in estrogen-dependent breast cancer cell movement. In T47-D breast cancer cells, E2 rapidly enhances ezrin phosphorylation at Thr567 in a time- and concentration-dependent manner. The signalling cascade implicated in this action involves estrogen receptor (ER) interaction with the non-receptor tyrosine kinase c-Src, which activates the phosphatidylinositol-3 kinase/Akt pathway and the small GTPase RhoA/Rho-associated kinase (ROCK-2) complex. E2 enhances the horizontal cell migration and invasion of T47-D breast cancer cells in three-dimensional matrices, which is reversed by transfection of cells with specific ezrin siRNAs. In conclusion, E2 promotes breast cancer cell movement and invasion by the activation of ezrin. These results provide novel insights into the effects of estrogen on breast cancer progression and highlight potential targets to treat endocrine-sensitive breast cancers

Monotone iteration scheme and its application to partial differential equation systems with mixed nonlocal and degenerate diffusions

A monotone iteration scheme for traveling waves based on ordered upper and lower solutions is derived for a class of nonlocal dispersal system with delay. Such system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species. An example of such system is studied in detail. We show the existence of the traveling wave solutions for this system by this iteration scheme. In addition, we study the minimal wave speed, uniqueness, strict monotonicity and asymptotic behavior of the traveling wave solutions

Robust and Blind Audio Watermarking Algorithm in Dual Domain for Overcoming Synchronization Attacks

How to effectively resist synchronization attacks is the most challenging topic in the research of robust watermarking algorithms. A robust and blind audio watermarking algorithm for overcoming synchronization attacks is proposed in dual domain by considering time domain and transform domain. Based on analysing the characteristics of synchronization attacks, an implicit synchronization mechanism (ISM) is developed in the time domain, which can effectively track the appropriate region for embedding and extracting watermarks. The data in this region will be subjected to discrete cosine transform (DCT) and singular value decomposition (SVD) in turn to obtain the eigenvalue that can be utilized to carry watermarks. In order to extract the watermark blindly, the eigenvalue will be quantized. Genetic algorithm (GA) is utilized to optimize the quantization step to balance both transparency and robustness. The experimental results confirm that the proposed algorithm not only withstands various conventional signal processing operations but also resists malicious synchronization attacks, such as time scale modification (TSM), pitch-shifting modification (PSM), jittering, and random cropping. Especially, it can overcome TSM with strength from −30% to +30%, which is much higher than the standard of the International Federation of the Phonographic Industry (IFPI) and far superior to the other algorithms in related papers

Data Uploading Strategy for Underwater Wireless Sensor Networks

Underwater wireless sensor networks (UWSNs) have become a popular research topic due to the challenges of underwater communication. The existing mechanisms for collecting data from UWSNs focus on reducing the data redundancy and communication energy consumption, while ignoring the problem of energy-saving transmission after compression. In order to improve the efficiency of data collection, we propose a data uploading decision-making strategy based on the high similarity of the collected data and the energy consumption of the high similarity data compression. This decision-making strategy efficiently optimizes the energy consumption of the networks. By analyzing the data similarity, the quality of network communication, and uploading energy consumption, the decision-making strategy provides an energy-efficient data upload strategy for underwater nodes, which reduces the energy consumption in various network settings. The simulation results show that compared with several existing data compression and uploading methods, the proposed data upload methods has better energy saving effect in different network scenarios

An On-Site-Based Opportunistic Routing Protocol for Scalable and Energy-Efficient Underwater Acoustic Sensor Networks

With the advancements in wireless sensor networks and the Internet of Underwater Things (IoUT), underwater acoustic sensor networks (UASNs) have attracted much attention, which has also been widely used in marine engineering exploration and disaster prevention. However, UASNs still face many challenges, including high propagation latency, limited bandwidth, high energy consumption, and unreliable transmission, influencing the good quality of service (QoS). In this paper, we propose a routing protocol based on the on-site architecture (SROA) for UASNs to improve network scalability and energy efficiency. The on-site architecture adopted by SROA is different from most architectures in that the data center is deployed underwater, which makes the sink nodes closer to the data source. A clustering method is introduced in SROA, which makes the network adapt to the changes in the network scale and avoid single-point failure. Moreover, the Q-learning algorithm is applied to seek optimal routing policies, in which the characteristics of underwater acoustic communication such as residual energy, end-to-end delay, and link quality are considered jointly when constructing the reward function. Furthermore, the reduction of packet retransmissions and collisions is advocated using a waiting mechanism developed from opportunistic routing (OR). The SROA realizes opportunistic routing to choose candidate nodes and coordinate packet forwarding among candidate nodes. The scalability of the proposed routing protocols is also analyzed by varying the network size and transmission range. According to the evaluation results, with the network scale ranging from 100 to 500, the SROA outperforms the existing routing protocols, extensively decreasing energy consumption and end-to-end delay