Significant improvement of physicians' knowledge and clinical practice: an opportune, effective, and convenient continuing medical education program on functional dyspepsia.

Aims: This cohort study aimed to explore the effect of a one-day online continuing medical education (CME) on the improvement of physicians' knowledge and clinical practice on functional dyspepsia (FD). Methods: Physicians were invited to participate in this CME via medical education applications. FD training videos made in advance were sent to participants via a weblink. Before and after training, participants were required to finish the FD knowledge test and provide case information of FD patients. McNemar test, Wilcoxon rank-sum test, Freidman test, Chi-square test, quantile regression, and generalized estimating equations (GEE) were used to perform statistical analysis. Results: There were 397 of 430 (92.33%) physicians finished this CME program. The total score of the FD knowledge test after training was significantly higher compared with before training [488.3 (468.3-510.0) vs. 391.7 (341.7-450.0), p < 0.001]. Particularly, physicians from primary hospitals show more increase in total scores than physicians from secondary and tertiary hospitals. According to the GEE model, receiving this online training was an independent predictor of physicians' choice of upper gastrointestinal endoscopy in patients with FD [OR 1.73, 95%CI (1.09-2.73), p = 0.020], especially in PDS. Also, it was an independent predictor of physicians' choice of acid-suppressive drugs in patients with FD [OR 1.30, 95%CI (1.03-1.63), p = 0.026], especially in EPS and PDS overlapping EPS. Conclusion: This one-day online CME program effectively and conveniently improved physicians' knowledge and clinical practice, providing new ideas for future CME and facilitating precise clinical management of FD patients with different subtypes especially in primary hospitals.

YAP1 expression in colorectal cancer confers the aggressive phenotypes via its target genes.

Yes-associated protein1 (YAP1), a downstream effector of the Hippo pathway, is over-expressed in several types of malignancies. We analyzed retrospectively the TCGA database using 447 colorectal cancer (CRC) samples to determine the correlation between YAP1 expression level and CRC patient prognosis. YAP1-enforced expressed CRC cell lines were constructed using the lentivirus particles containing a YAP1 insert. YAP1 was highly expressed in CRC cancerous tissues and is associated with distant metastasis of CRC patients. Kaplan - Meier analysis indicated that CRC patients with a higher YAP1 expression group (n = 104) had worse disease-free survival (DFS) and overall survival (OS) than lower YAP1 expression group (n = 343) (p = 0.008 and p = 0.022). Univariate and multivariate analysis indicated that the elevated YAP1 expression predicted the aggressive phenotype and was an independent indicator for OS and DFS of CRC patients. YAP1 over-expression in CRC cells enhanced their migration and invasion significantly which can be reversed by AXL, CTGF, or CYR61 interference. The study suggested that YAP1 affected the prognosis of CRC patients and controlled the abilities of invasion and migration of CRC cells via its target genes AXL, CTGF, and CYR61.

Detecting protein complexes with multiple properties by an adaptive harmony search algorithm.

BACKGROUND: Accurate identification of protein complexes in protein-protein interaction (PPI) networks is crucial for understanding the principles of cellular organization. Most computational methods ignore the fact that proteins in a protein complex have a functional similarity and are co-localized and co-expressed at the same place and time, respectively. Meanwhile, the parameters of the current methods are specified by users, so these methods cannot effectively deal with different input PPI networks. RESULT: To address these issues, this study proposes a new method called MP-AHSA to detect protein complexes with Multiple Properties (MP), and an Adaptation Harmony Search Algorithm is developed to optimize the parameters of the MP algorithm. First, a weighted PPI network is constructed using functional annotations, and multiple biological properties and the Markov cluster algorithm (MCL) are used to mine protein complex cores. Then, a fitness function is defined, and a protein complex forming strategy is designed to detect attachment proteins and form protein complexes. Next, a protein complex filtering strategy is formulated to filter out the protein complexes. Finally, an adaptation harmony search algorithm is developed to determine the MP algorithm's parameters automatically. CONCLUSIONS: Experimental results show that the proposed MP-AHSA method outperforms 14 state-of-the-art methods for identifying protein complexes. Also, the functional enrichment analyses reveal that the protein complexes identified by the MP-AHSA algorithm have significant biological relevance.

TET2-BCLAF1 transcription repression complex epigenetically regulates the expression of colorectal cancer gene Ascl2 via methylation of its promoter.

Ascl2 has been shown to be involved in tumorigenesis in colorectal cancer (CRC), although its epigenetic regulatory mechanism is largely unknown. Here, we found that methylation of the Ascl2 promoter (bp -1670 ∼ -1139) was significantly increased compared to the other regions of the Ascl2 locus in CRC cells and was associated with elevated Ascl2 mRNA expression. Furthermore, we found that promoter methylation was predictive of CRC patient survival after analyzing DNA methylation data, RNA-Seq data, and clinical data of 410 CRC patient samples from the MethHC database, the MEXPRESS database, and the Cbioportal website. Using the established TET methylcytosine dioxygenase 2 (TET2) knockdown and ectopic TET2 catalytic domain-expression cell models, we performed glucosylated hydroxymethyl-sensitive quatitative PCR (qPCR), real-time PCR, and Western blot assays to further confirm that hypermethylation of the Ascl2 promoter, and elevated Ascl2 expression in CRC cells was partly due to the decreased expression of TET2. Furthermore, BCLAF1 was identified as a TET2 interactor in CRC cells by LC-MS/MS, coimmunoprecipitation, immunofluorescence colocalization, and proximity ligation assays. Subsequently, we found the TET2-BCLAF1 complex bound to multiple elements around CCGG sites at the Ascl2 promoter and further restrained its hypermethylation by inducing its hydroxymethylation using chromatin immunoprecipitation-qPCR and glucosylated hydroxymethyl-qPCR assays. Finally, we demonstrate that TET2-modulated Ascl2-targeted stem gene expression in CRC cells was independent of Wnt signaling. Taken together, our data suggest an additional option for inhibiting Ascl2 expression in CRC cells through TET2-BCLAF1-mediated promoter methylation, Ascl2-dependent self-renewal of CRC progenitor cells, and TET2-BCLAF1-related CRC progression.

An Ensemble Learning Framework for Detecting Protein Complexes From PPI Networks.

Detecting protein complexes is one of the keys to understanding cellular organization and processes principles. With high-throughput experiments and computing science development, it has become possible to detect protein complexes by computational methods. However, most computational methods are based on either unsupervised learning or supervised learning. Unsupervised learning-based methods do not need training datasets, but they can only detect one or several topological protein complexes. Supervised learning-based methods can detect protein complexes with different topological structures. However, they are usually based on a type of training model, and the generalization of a single model is poor. Therefore, we propose an Ensemble Learning Framework for Detecting Protein Complexes (ELF-DPC) within protein-protein interaction (PPI) networks to address these challenges. The ELF-DPC first constructs the weighted PPI network by combining topological and biological information. Second, it mines protein complex cores using the protein complex core mining strategy we designed. Third, it obtains an ensemble learning model by integrating structural modularity and a trained voting regressor model. Finally, it extends the protein complex cores and forms protein complexes by a graph heuristic search strategy. The experimental results demonstrate that ELF-DPC performs better than the twelve state-of-the-art approaches. Moreover, functional enrichment analysis illustrated that ELF-DPC could detect biologically meaningful protein complexes. The code/dataset is available for free download from https://github.com/RongquanWang/ELF-DPC.

An Improved Memetic Algorithm for Detecting Protein Complexes in Protein Interaction Networks.

Identifying the protein complexes in protein-protein interaction (PPI) networks is essential for understanding cellular organization and biological processes. To address the high false positive/negative rates of PPI networks and detect protein complexes with multiple topological structures, we developed a novel improved memetic algorithm (IMA). IMA first combines the topological and biological properties to obtain a weighted PPI network with reduced noise. Next, it integrates various clustering results to construct the initial populations. Furthermore, a fitness function is designed based on the five topological properties of the protein complexes. Finally, we describe the rest of our IMA method, which primarily consists of four steps: selection operator, recombination operator, local optimization strategy, and updating the population operator. In particular, IMA is a combination of genetic algorithm and a local optimization strategy, which has a strong global search ability, and searches for local optimal solutions effectively. The experimental results demonstrate that IMA performs much better than the base methods and existing state-of-the-art techniques. The source code and datasets of the IMA can be found at https://github.com/RongquanWang/IMA.

Characterization of the intestinal digesta and mucosal microbiome of the grass carp (Ctenopharyngodon idella).

The intestinal microbiome plays a pivotal role in the nutritional digestion and metabolism of the grass carp (Ctenopharyngodon idella). Here, we characterized the digesta and mucosal microbiome of the anterior, middle, and posterior intestine of the grass carp, using 16S rRNA next-generation sequencing. Based on 16S rRNA amplicon data, Proteobacteria, Firmicutes and Bacteroides were the dominant phyla in the intestine of grass carp. Our results also showed that microbial communities of the middle intestine exhibited higher alpha diversity indices compared with the anterior and posterior intestine. The clustering of microbial communities that had either colonized in the digesta or were attached to the mucosa, were significantly tighter in the posterior intestine, based on average unweighted Unifrac distances (P < 0.05). The digesta or mucosa of the anterior and middle intestines were similar in microbial composition, but were significantly different to the posterior intestine (P < 0.05). In digesta and mucosa samples from the posterior intestine, we observed a significantly increased abundance of cellulose-degrading microbiomes, such as Bacteroides, Clostridiales and Spirochaetia (P < 0.05). Our results suggested that the microbiomes of the posterior intestine, either attached to the mucosa or colonized in the digesta, were distinct from the microbiomes of the anterior and middle intestine in grass carp.

The Diagnosis Performance of the TCM Syndromes of Irritable Bowel Syndrome by Gastroenterologists Based on Modified Simple Criteria Compared to TCM Practitioners: A Prospective, Multicenter Preliminary Study.

PURPOSE: Traditional Chinese medicine (TCM) including Chinese patent medicine has been widely used to treat irritable bowel syndrome (IBS). Syndrome differentiation is the essence of TCM. However, the diagnostic ability of gastroenterologists to detect TCM syndromes in IBS in China remains unknown. The aim of this study was to investigate the ability of gastroenterologists to diagnose the TCM syndromes of IBS based on modified simple criteria compared with TCM practitioners. METHODS: Patients meeting the Rome III criteria for IBS-D or IBS-C were recruited from six tertiary referral centers between January 2016 and December 2017. After learning the diagnosis criteria of the TCM syndromes in IBS, gastroenterologists first diagnosed the syndromes of the enrolled patients. Subsequently, the patients were diagnosed by TCM practitioners. The rate of agreement between the gastroenterologists and TCM practitioners was analyzed. In addition, demographic data and the distribution of TCM syndrome types in IBS were also analyzed. RESULTS: A total of 178 patients (93 males and 85 females), including 131 patients with IBS-D and 47 patients with IBS-C, were enrolled in this study. The rate of agreement of the syndrome diagnosis between the gastroenterologists and TCM practitioners was 84.3%. The diagnosis consistency rates among IBS-D patients and IBS-C patients were 87.0% and 76.5%, respectively. The most common TCM syndrome type in IBS-D patients was liver depression and spleen deficiency syndrome (27.5%), followed by spleen-yang deficiency syndrome (19.8%). Dryness and heat in intestine syndrome was the most common TCM syndrome in IBS-C patients (57.4%). CONCLUSIONS: Gastroenterologists had good diagnostic agreement with TCM practitioners for diagnosing TCM syndrome types in IBS after learning the diagnostic criteria. This knowledge can aid gastroenterologists in selecting suitable Chinese patent medicine to treat IBS.

16S rRNA sequencing analysis of the correlation between the intestinal microbiota and body-mass of grass carp (Ctenopharyngodon idella).

There appears to be a close correlation between intestinal microbiotas and obesity. Still, our understanding of the relationship between the intestinal microbiota and body-mass in grass carp (Ctenopharyngodon idella) remains limited. Herein, we explored this association in the anterior, middle, and posterior intestine of cohabitating grass carp by using next-generation sequencing of the 16S rRNA gene. The results showed that alpha diversity indices of the low-weight-gain (LWG) groups were higher than that of the high-weight-gain (HWG) groups. HWG groups possessed the decreased ratio of Bacteroidetes to Firmicutes compared with that in the LWG groups. Principal coordinate analysis (PCoA) and analysis of similarities (ANOSIM) revealed that there were significant differences between the HWG and LWG groups. Furthermore, linear discriminant analysis (LDA) coupled with effect size (LEfSe) showed that the order Clostridiales were significantly abundant in the HWG groups. Phylogenetic molecular ecology networks (pMENs) showed a lower average path distance (GD), higher average clustering coefficient (avgCC), and higher average degree (avgK) in the HWG group. Our results suggested that there appeared to be a tight correlation between the intestinal microbiota and body-mass in grass carp. The study provides a referable resource for establishing the relationship between intestinal microbiotas and economic traits, which also lays a foundation for the progress of new fish probiotic in the future.

Identification, characterization, and immunological analysis of complement component 4 from grass carp (Ctenopharyngodon idella).

Complement component 4 (C4) has critical immunological functions in vertebrates. In the current study, a C4 homolog (gcC4) was identified in grass carp (Ctenopharyngodon idella). The full-length 5458 bp gcC4 cDNA contained a 5148 bp open reading frame (ORF) encoding a protein of 1715 amino acids with a signal peptide and eight conservative domains. The gcC4 protein has a high level of identity with other fish C4 counterparts and is phylogenetically clustered with cyprinid fish C4. The gcC4 transcript shows wide tissue distribution and is inducible by Aeromonas hydrophila in vivo and in vitro. Furthermore, its expression also fluctuates upon lipopolysaccharide or flagellin stimulation in vitro. During infection, the gcC4 protein level decreases or increases to varying degrees, and the intrahepatic C4 expression location changes. With gcC4 overexpression, interleukin 1 beta, tumor necrosis factor alpha, and interferon transcripts are all upregulated by A. hydrophila infection. Meanwhile, overexpression of gcC4 reduces bacterial invasion or proliferation. Moreover, gcC4 may activate the NF-κB signaling pathway. These findings demonstrate the vital role of gcC4 in the innate immunity of grass carp.

Identifying protein complexes based on an edge weight algorithm and core-attachment structure.

BACKGROUND: Protein complex identification from protein-protein interaction (PPI) networks is crucial for understanding cellular organization principles and functional mechanisms. In recent decades, numerous computational methods have been proposed to identify protein complexes. However, most of the current state-of-the-art studies still have some challenges to resolve, including their high false-positives rates, incapability of identifying overlapping complexes, lack of consideration for the inherent organization within protein complexes, and absence of some biological attachment proteins. RESULTS: In this paper, to overcome these limitations, we present a protein complex identification method based on an edge weight method and core-attachment structure (EWCA) which consists of a complex core and some sparse attachment proteins. First, we propose a new weighting method to assess the reliability of interactions. Second, we identify protein complex cores by using the structural similarity between a seed and its direct neighbors. Third, we introduce a new method to detect attachment proteins that is able to distinguish and identify peripheral proteins and overlapping proteins. Finally, we bind attachment proteins to their corresponding complex cores to form protein complexes and discard redundant protein complexes. The experimental results indicate that EWCA outperforms existing state-of-the-art methods in terms of both accuracy and p-value. Furthermore, EWCA could identify many more protein complexes with statistical significance. Additionally, EWCA could have better balance accuracy and efficiency than some state-of-the-art methods with high accuracy. CONCLUSIONS: In summary, EWCA has better performance for protein complex identification by a comprehensive comparison with twelve algorithms in terms of different evaluation metrics. The datasets and software are freely available for academic research at https://github.com/RongquanWang/EWCA .

Myeloid differentiation factor 88 (Myd88) is involved in the innate immunity of black carp (Mylopharyngodon piceus) defense against pathogen infection.

Myeloid differentiation factor 88 (MyD88) is an important transduction protein in the Toll-like receptor signaling pathway. In this study, we identified the cDNA of the MpMyD88 gene in black carp. We found that MpMyD88 was widely distributed in the tissues tested and showed significant immune responses both in vitro and in vivo after stimulation with bacterial and pathogen-associated molecular patterns. After MpMyD88 overexpression/silencing, proinflame-matory cytokines (TNF-α, IFN-α, IL-6, and IL-8) also showed significant up-regulation/down-regulation. Moreover, we found that the antibacterial ability of cells over-expressing MpMyD88 was significantly stronger than that of control cells, while that of silenced MpMyD88 was significantly lower than that in control cells. Besides, we found that the overexpression of MpMyD88 significantly increased the activity of NF-κB. These results indicate that MpMyD88 plays an important role in the innate immune response.

A seed-extended algorithm for detecting protein complexes based on density and modularity with topological structure and GO annotations.

BACKGROUND: The detection of protein complexes is of great significance for researching mechanisms underlying complex diseases and developing new drugs. Thus, various computational algorithms have been proposed for protein complex detection. However, most of these methods are based on only topological information and are sensitive to the reliability of interactions. As a result, their performance is affected by false-positive interactions in PPINs. Moreover, these methods consider only density and modularity and ignore protein complexes with various densities and modularities. RESULTS: To address these challenges, we propose an algorithm to exploit protein complexes in PPINs by a Seed-Extended algorithm based on Density and Modularity with Topological structure and GO annotations, named SE-DMTG to improve the accuracy of protein complex detection. First, we use common neighbors and GO annotations to construct a weighted PPIN. Second, we define a new seed selection strategy to select seed nodes. Third, we design a new fitness function to detect protein complexes with various densities and modularities. We compare the performance of SE-DMTG with that of thirteen state-of-the-art algorithms on several real datasets. CONCLUSION: The experimental results show that SE-DMTG not only outperforms some classical algorithms in yeast PPINs in terms of the F-measure and Jaccard but also achieves an ideal performance in terms of functional enrichment. Furthermore, we apply SE-DMTG to PPINs of several other species and demonstrate the outstanding accuracy and matching ratio in detecting protein complexes compared with other algorithms.

Complement component 3 (C3): An important role in grass carp (Ctenopharyngodon idella) experimentally exposed to Aeromonas hydrophila.

Complement is traditionally recognized as part of the innate immune system, defending the host against the invasion of foreign pathogens. In complement system, C3 (complement component 3) is a central component. Therefore, research into C3 can help us better understand the functions of fish complement system. In this study, we detected the grass carp C3 (gcC3) mRNA expression in all sample tissues from healthy grass carp, which was highest in the liver, followed by the heart and the spleen, and lowest in the muscle, head kidney, trunk kidney, blood and intestine. After infection with Aeromonas hydrophila, gcC3 mRNA expression levels were significantly upregulated in the gill, liver, spleen, intestine, trunk kidney and head kidney. Interestingly, C3 protein levels were downregulated and subsequently upregulated in the liver and serum. Histologically, C3 protein at 24 h pi was over expressed in necrotic liver sites, and the liver index (LI) at this point was significantly higher than that of the control. These findings are indicated that C3 plays an important role in the immune response of grass carp after A. hydrophila infection, and C3 protein may play an assistant role in repairing liver tissues from A. hydrophila injury.

Transcriptome analysis and histopathology of black carp (Mylopharyngodon piceus) spleen infected by Aeromonas hydrophila.

Aeromonas hydrophila causes serious economic losses to the black carp (Mylopharyngodon piceus) industry. In this study, we analyzed the spleen of disease-resistant and susceptible black carp by RNA-seq. Overall, a total of 5243 terms were enriched in the gene ontology (GO) analysis, and 323 related pathways were found in the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. A total of 1935 differentially expressed genes were found and were primarily involved in cell adhesion, pathogen recognition, cellular immunity, cytokines, complement systems, and iron transport. Sixteen of the differently expressed genes involved in the immune response and the accuracy of the transcriptome data were further validated by quantitative real-time PCR (qRT-PCR). We observed Tissue sections of the spleen infected with A. hydrophila and the control group and found that the spleen of the infected group had necrosis.

Predicting overlapping protein complexes based on core-attachment and a local modularity structure.

BACKGROUND: In recent decades, detecting protein complexes (PCs) from protein-protein interaction networks (PPINs) has been an active area of research. There are a large number of excellent graph clustering methods that work very well for identifying PCs. However, most of existing methods usually overlook the inherent core-attachment organization of PCs. Therefore, these methods have three major limitations we should concern. Firstly, many methods have ignored the importance of selecting seed, especially without considering the impact of overlapping nodes as seed nodes. Thus, there may be false predictions. Secondly, PCs are generally supposed to be dense subgraphs. However, the subgraphs with high local modularity structure usually correspond to PCs. Thirdly, a number of available methods lack handling noise mechanism, and miss some peripheral proteins. In summary, all these challenging issues are very important for predicting more biological overlapping PCs. RESULTS: In this paper, to overcome these weaknesses, we propose a clustering method by core-attachment and local modularity structure, named CALM, to detect overlapping PCs from weighted PPINs with noises. Firstly, we identify overlapping nodes and seed nodes. Secondly, for a node, we calculate the support function between a node and a cluster. In CALM, a cluster which initially consists of only a seed node, is extended by adding its direct neighboring nodes recursively according to the support function, until this cluster forms a locally optimal modularity subgraph. Thirdly, we repeat this process for the remaining seed nodes. Finally, merging and removing procedures are carried out to obtain final predicted clusters. The experimental results show that CALM outperforms other classical methods, and achieves ideal overall performance. Furthermore, CALM can match more complexes with a higher accuracy and provide a better one-to-one mapping with reference complexes in all test datasets. Additionally, CALM is robust against the high rate of noise PPIN. CONCLUSIONS: By considering core-attachment and local modularity structure, CALM could detect PCs much more effectively than some representative methods. In short, CALM could potentially identify previous undiscovered overlapping PCs with various density and high modularity.

R-spondin1/Wnt-enhanced Ascl2 autoregulation controls the self-renewal of colorectal cancer progenitor cells.

The Wnt signaling pathway controls stem cell identity in the intestinal epithelium and cancer stem cells (CSCs). The transcription factor Ascl2 (Wnt target gene) is fate decider of intestinal cryptic stem cells and colon cancer stem cells. It is unclear how Wnt signaling is translated into Ascl2 expression and keeping the self-renewal of CRC progenitor cells. We showed that the exogenous Ascl2 in colorectal cancer (CRC) cells activated the endogenous Ascl2 expression via a direct autoactivatory loop, including Ascl2 binding to its own promoter and further transcriptional activation. Higher Ascl2 expression in human CRC cancerous tissues led to greater enrichment in Ascl2 immunoprecipitated DNA within the Ascl2 promoter in the CRC cancerous sample than the peri-cancerous mucosa. Ascl2 binding to its own promoter and inducing further transcriptional activation of the Ascl2 gene was predominant in the CD133+CD44+ CRC population. R-spondin1/Wnt activated Ascl2 expression dose-dependently in the CD133+CD44+ CRC population, but not in the CD133-CD44- CRC population, which was caused by differences in Ascl2 autoregulation under R-spondin1/Wnt activation. R-spondin1/Wnt treatment in the CD133+CD44+ or CRC CD133-CD44- populations exerted a different pattern of stemness maintenance, which was defined by alterations of the mRNA levels of stemness-associated genes, the protein expression levels (Bmi1, C-myc, Oct-4 and Nanog) and tumorsphere formation. The results indicated that Ascl2 autoregulation formed a transcriptional switch that was enhanced by Wnt signaling in the CD133+CD44+ CRC population, thus conferring their self-renewal.

A Randomized, Double-Blind, Multicenter, Placebo-Controlled Trial of Qi-Zhi-Wei-Tong Granules on Postprandial Distress Syndrome-Predominant Functional Dyspepsia.

BACKGROUND: Functional dyspepsia (FD) is a common upper gastrointestinal disorder worldwide, but the current treatments for FD are still unsatisfactory. The aims of this study were to investigate the efficacy and safety of Qi-Zhi-Wei-Tong granules in patients with postprandial distress syndrome (PDS)-predominant FD. METHODS: The study was conducted as a randomized, double-blinded, multicenter, placebo-controlled design in 197 patients with PDS. All participants received placebo treatment for 1 week. Patients whose total symptom score decreased by <50% after the placebo treatment were recruited into the 4-week treatment period, in which they were randomly assigned to be treated with either Qi-Zhi-Wei-Tong granules or placebo. The patients were then followed for 2 weeks without any treatment. Dyspeptic symptoms were scored at weeks 2 and 4 during the random treatment period and 2 weeks after the treatment. Anxiety and depression symptoms were also scored and compared. RESULTS: (1) The total effective rates in the Qi-Zhi-Wei-Tong granules group at weeks 2 and 4 during the random treatment period and 2 weeks after treatment were all significantly higher than those in the placebo group (38.82% vs. 8.75%, P < 0.001; 69.14% vs. 16.25%, P < 0.001; 77.65% vs. 21.25%, P < 0.001). (2) The total dyspeptic symptoms scores in the Qi-Zhi-Wei-Tong granules group at weeks 2 and 4 and 2 weeks after treatment were significantly lower than those in the placebo group. (3) The severity and frequency of each dyspeptic symptom at weeks 2 and 4 and the follow-up period were all significantly lower than those in the placebo group. (4) The anxiety scores in the Qi-Zhi-Wei-Tong granules group were significantly lower than those in the placebo group. (5) Qi-Zhi-Wei-Tong granules did not have more adverse effects than the placebo. CONCLUSION: Qi-Zhi-Wei-Tong granules offer significant symptomatic improvement in PDS with no more adverse effects than placebo. TRIAL REGISTRATION: https://clinicaltrials.gov/, NCT02460601.

Complement component Bf/C2b gene mediates immune responses against Aeromonas hydrophila in grass carp Ctenopharyngodon idella.

The complement system is a significant component of innate immunity. Here, we identified a Bf/C2 homolog (gcBf/C2b) in grass carp. gcBf/C2b shares a high similarity with Bf/C2b counterparts in other teleosts. gcBf/C2b transcription was widely distributed in different tissues, induced by Aeromonas hydrophila in vivo and in vitro, and affected by lipopolysaccharide and flagellin stimulation in vitro. In cells over-expressing gcBf/C2b, transcript levels of all components except gcC5 were significantly enhanced, and gcBf/C2b, gcIL1ß, gcTNF-α, gcIFN, gcCD59, gcC5aR1, and gcITGß-2 were significantly upregulated after A. hydrophila challenge or stimulation with bacterial pathogen-associated molecular patterns (PAMPs). However, gcBf/C2b in interference cells down-regulated the transcript levels after A. hydrophila challenge, and gcBf/C2b induced NF-κB signaling. These findings indicate the vital role of gcBf/C2b in innate immunity in grass carp.