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Objective. Inflammatory responses play important roles in the pathogenesis of atherosclerosis. The purpose of this study was to investigate the relationship between microRNA-146b-3p (miR-146b-3p) and inflammatory factors in thrombosis. Method. THP-1 cells were cultured in vitro, Western blot was used to determine the protein levels of COX-2 and p38MAPK in the cells, and real-time PCR was used to detect the mRNA expression of miRNA-146b-3p and COX-2. A lentiviral expression vector of miRNA-146b-3p and its inhibitor were constructed to transfect THP-1 cells. COX-2 and p38MAPK expression in transfected cells was detected by Western blot and real-time PCR, respectively. Results. Ang II and TNF-α could elevate the expression of COX-2 in monocytes. The expression of COX-2 was upregulated by p38MAPK, which could be phosphorylated by Ang II, while there was an increasing tendency of p38MAPK phosphorylation after TNF-α stimulation. In addition, COX-2 expression and P38MAPK phosphorylation could be downregulated by miRNA-146b-3p and upregulated by the miRNA-146b-3p inhibitor. Ang II could increase miR-146b-3p expression, although there was no significant difference; however, the expression of miR-146b-3p was enhanced significantly by TNF-α. Conclusion. Our data implied that altered expression of miR-146b-3p was closely related to the progression of inflammation mediating the P38MAPK/COX-2 pathway. We suggest that the miR-146b-3p/p38MAPK/COX-2 pathway plays a key role in inflammation and arterial thrombosis. [ABSTRACT FROM AUTHOR]

Beta-defensins (β-defensins) are small cationic amphiphilic peptides that are widely distributed in plants, insects, and vertebrates, and are important for their antimicrobial properties. In this study, the β-defensin ( On β-defensin) gene of the Nile tilapia ( Oreochromis niloticus ) was cloned from spleen tissue. On β-defensin has a genomic DNA sequence of 674 bp and produces a cDNA of 454 bp. Sequence alignments showed that On β-defensin contains three exons and two introns. Sequence analysis of the cDNA identified an open reading frame of 201 bp, encoding 66 amino acids. Bioinformatic analysis showed that On β-defensin encodes a cytoplasmic protein molecule containing a signal peptide. The deduced amino acid sequence of this peptide contains six conserved cysteine residues and two conserved glycine residues, and shows 81.82% and 78.33% sequence similarities with β-defensin-1 of fugu ( Takifugu rubripes ) and rainbow trout ( Oncorhynchus mykiss ), respectively. Real-time quantitative PCR showed that the level of On β-defensin expression was highest in the skin (307.1-fold), followed by the spleen (77.3-fold), kidney (17.8-fold), and muscle (16.5-fold) compared to controls. By contrast, low levels of expression were found in the liver, heart, intestine, stomach, and gill (< 3.0-fold). Artificial infection of tilapia with Streptococcus agalactiae (group B streptococcus [GBS] strain) resulted in a significantly upregulated expression of On β-defensin in the skin, muscle, kidney, and gill. In vitro antimicrobial experiments showed that a synthetic On β-defensin polypeptide had a certain degree of inhibitory effect on the growth of Escherichia coli DH5α and S. agalactiae . The results indicate that On β-defensin plays a role in immune responses that suppress or kill pathogens. [ABSTRACT FROM AUTHOR]

Aim The aim of this study was to explore the genes and pathways involved in the aggressive breast cancer cells. Methods The gene expression profiles of GSE40057, including four aggressive breast cell lines and six less aggressive cell lines, were downloaded from the Gene Expression Omnibus ( GEO) database. The gene differential expression analysis was carried out with limma software with the method of Bayes for multiple tests. The gene ontology ( GO) term enrichment and pathway cross-talk analysis were performed with the online tool of DAVID and Cytoscape software. Results A total of 401 differentially expressed genes ( DEG), such as pentraxin 3 ( PTX3), snail family zinc finger 2 ( SNAI2), interleukin-8/6 ( IL-8/6), osteonectin ( SPARC), matrix metallopeptidase-1 ( MMP-1) and Ras-related protein Rab-25 ( Rab 25), were identified between aggressive and less aggressive cell lines. They were mainly enriched in the GO terms of response to wounding, negative regulation of cell proliferation and calcium binding. Pathways in cancer dysfunctionally interacted with glyoxylate and dicarboxylate metabolism ( P < 0.0001), basal transcription factors ( P < 0.0001), tyrosine metabolism ( P < 0.0001), calcium signaling pathway ( P = 0.0021), FcγR-mediated phagocytosis ( P = 0.0022), metabolism of xenobiotics by cytochrome P450 ( P = 0.0097) and phagosome ( P = 0.0102). Conclusion The screened aggressive cancer-associated DEG ( PTX3, SNAI2, IL-8/6, SPARC, MMP-1 and Rab25) and significant pathways (calcium signaling pathway, tyrosine metabolism, alanine, aspartate and glutamate metabolism) give us new insights into the mechanism of aggressive breast cancer cells, and these DEG may become promising target genes in the treatment of metastatic breast cancer. [ABSTRACT FROM AUTHOR]

Leucine-rich repeat containing G protein-coupled receptor 4 (LGR4) promotes the Wnt signaling through interaction with R-spondins or norrin. Using PCR amplification from rat ovarian cDNAs, we identified a naturally occurring Lgr4 splice variant encoding only the ectodomain of Lgr4, which was named Lgr4-ED. Lgr4-ED can be detected as a secreted protein in the extracts from rodent and bovine postnatal gonads, suggesting conservation of Lgr4-ED in mammals. Recombinant Lgr4-ED purified from the conditioned media of transfected 293T cells was found to dose-dependently inhibit the LGR4-mediated Wnt signaling induced by RSPO2 or norrin, suggesting that it is capable of ligand absorption and could have a potential role as an antagonist. Intraperitoneal injection of purified recombinant Lgr4-ED into newborn mice was found to significantly decrease the testicular expression of estrogen receptor alpha and aquaporin 1, which is similar to the phenotype found in Lgr4-null mice. Administration of recombinant Lgr4-ED to superovulated female rats can also decrease the expression of estrogen receptor alpha, aquaporin 1, LH receptor and other key steroidogenic genes as well as bring about the suppression of progesterone production. Thus, these findings suggest that endogenously expressed Lgr4-ED may act as an antagonist molecule and help to fine-tune the R-spondin/norrin-mediated Lgr4-Wnt signaling during gonadal development. [ABSTRACT FROM AUTHOR]

Numerous reports have found that long non-coding (lnc) RNAs were associated with pancreatic cancer (PC) initiation and development. The lncRNA titin antisense RNA 1 (TTN-AS1) was identified as a tumor promoter in certain types of cancer; however, its role and mechanism in PC remain unclear. The aim of the present study was to investigate the role of TTN-AS1 in PC and elucidate the underlying mechanism. Reverse transcription-quantitative PCR analysis was performed to examine the mRNA expression level of TTN-AS1, microRNA(miR)-589-5p and forkhead box protein 1 (FOXP1). Knockdown experiments were performed to examine the effect of TTN-AS1 on PC cell proliferation, migration and invasion. Luciferase reporter assays validated the binding of miR-589-5p to TTN-AS1 and FOXP1. Chromatin immunoprecipitation and luciferase reporter assays confirmed the binding ability of FOXP1 to the TTN-AS1 promoter. As a result, TTN-AS1 and FOXP1 were found to be upregulated in PC cell lines and tissues, while miR-589-5p was expressed at low levels. Knockdown experiments indicated the suppressive effect of TTN-AS1 knockdown on cell proliferation, migration and invasion in PC cell lines. Further mechanistic research uncovered that TTN-AS1 functioned as a molecular sponge for miR-589-5p and its mRNA expression level in PC tissues was inversely associated with that of miR-589-5p. Furthermore, miR-589-5p was confirmed to target FOXP1. Of note, it was discovered that FOXP1 transcriptionally activated TTN-AS1 mRNA expression level. Taken together, the findings of the present study demonstrated that the new TTN-AS1/miR-589-5p/FOXP1 feedback loop may play an important role in PC. [ABSTRACT FROM AUTHOR]

Purpose: The objective of our study was to investigate the effect of 5,7-DMF on the accumulation of mitoxantrone (MX) in BCRP-expressing normal cells and to investigate its impact on the PK and tissue distribution of MX in mice. Methods: The in vitro effect of 5,7-DMF on MX accumulation was examined in MDCK cells transfected with BCRP. The pharmacokinetic and tissue distribution of mitoxantrone, with and without co-administration of 5,7-DMF or multiple flavonoid combinations, were determined in mice. Results: In the presence of 2.5 μM or 25 μM of 5,7-DMF, the intracellular concentration of MX was significantly increased in MDCK/Bcrp1 and MDCK/BCRP cells, but not in MDCK/Mock cells. The AUC values of MX in several tissues were significantly increased when MX was co-administered with 5,7-DMF. The most substantial elevations of MX AUC in the presence of 5,7-DMF occurred in the liver (94.5%) and kidneys (61.9%), which is in apparent agreement with the relatively high levels of mouse Bcrp1 expression in these two tissues. Conclusions: Bcrp1-mediated DMF-MX interactions occur both in vitro and in vivo. 5,7-DMF represents a novel and very promising chemosensitizing agent for the BCRP-mediated MDR due to its low toxicity and potent BCRP inhibition. [ABSTRACT FROM AUTHOR]

Abstract: Honokiol has been shown to possess a lot of pharmacologic benefits, including antioxidative, antiangiogenic and antineoplastic effects. In the present study, we investigated the anti-inflammatory effects of honokiol and the signaling mechanisms involved in lipopolysaccharide (LPS)-induced conditions in human renal mesangial cells (HRMCs). Honokiol did not significantly change HRMC viability when used at a concentration of <20μmol/l but markedly altered cell viability at concentrations of >40μmol/l. In this study, LPS treatment led to a marked upregulation of the levels of IL-1β, IL-18, TNF-α, TGF-β1, CCL2, CCL3, and CCL5 in HRMCs. The expression of COX-2, iNOS, and their products PGE2 and NO also increased. The upregulation of these molecules was significantly abolished by honokiol in a dose-dependent manner. Moreover, honokiol almost completely reversed IL-1β, CCL3, and NO expression at 10μmol/l, and IL-18, TNF-α, TGF-β1, and COX-2 expression at 20μmol/l. In addition, phospho-NF-κB p65 at Ser536, phospho-Akt, and phospho-p42/44 were dramatically suppressed by honokiol in LPS-treated HRMCs. These results indicate that honokiol can inhibit the LPS-induced expression of inflammatory cytokines and mediators in HRMCs. The anti-inflammatory mechanisms of honokiol are partly due to the suppression of the phospho-NF-κB p65, phospho-Akt and phospho-p42/44 pathways. [ABSTRACT FROM AUTHOR]

To promote the growth of Lactobacillus reuteri (L. reuteri), in this study, we optimized the culture using a single-factor experimental and response surface methodology. Then, the water extract of Stropharia rugosoannulata (WES) was used as an accelerant for L. reuteri HBM11-69 growth, and its effects on the growth and metabolism of the strain were investigated. Meanwhile, transcriptomics was used to analyze the gene expression of L. reuteri and its possible mechanisms. The optimal medium formulation for L. reuteri HBM11-69 was determined by single-factor experimental and response surface methodology, and the number of viable bacteria was 5 times higher than that of MRS medium. Furthermore, L. reuteri HBM11-69 exhibited the best growth with the viable bacterial number of 1.41 × 1010 CFU/mL and the content of short-chain fatty acids was the highest when 20 g/L of WES was added to the optimized medium. L. reuteri HBM11-69 cultures before and after WES addition were used for transcriptome analysis. The transcriptomic results showed that the differentially expressed genes BSU40060, BSU33510, spr1465 and BSU22120 were significantly up-regulated. The WES promoting proliferation of L. reuteri HBM11-69 is closely related to glucokinase, heavy-metal-associated domain-containing protein and phosphatidic acid biosynthetic. • L. reuteri HBM11-69 is high-density growth. • Water extract of Stropharia rugosoannulata (WES) is a new prebiotic. • Addition of WES promotes the proliferation of L. reuteri HBM11-69. [ABSTRACT FROM AUTHOR]

A gene regulatory network can be considered a dynamic cellular system which describes the behavior (development) of a living cell and depends completely on the current internal state plus any external inputs, if these exist. Although many details inside a cell are not precisely known, gene expression data on a genome scale provide useful insights into such a cellular system. With gene expression data, a wide variety of models, such as Boolean networks and differential/difference equations, have been proposed to model gene regulatory networks. In these previously proposed models, genes are viewed as the internal state variables of a cellular system. This viewpoint has suffered from the underestimation of the model parameters. In addition, these models ignore an important problem with a gene regulatory network — time delay. Instead, this paper proposes a state-space model with time delays for gene regulatory networks. The proposed model views genes as the observation variables, whose expression values depend on the current internal state variables and any external inputs. Bayesian information criterion (BIC) and probabilistic principal component analysis (PPCA) are used to estimate the number of internal state variables and their expression profiles from gene expression data. By constructing dynamic equations with time delays for the internal state variables and the relationships between the internal state variables and the observation variables (gene expression profiles), state-space models with time delays for gene regulatory networks are constructed. The parameters of the proposed model can be unambiguously identified from time-course gene expression data with a lower computational cost. The proposed model is applied to two time-course gene expression datasets, and two gene regulatory~networks are inferred, respectively. The analysis shows that the inferred gene regulatory networks have several features of the real gene regulatory networks, such as the stability, the robustness, and the periodicity. Further, compared to state-space models without time delays, the proposed model with time delays has better prediction accuracy. [ABSTRACT FROM AUTHOR]

Human metallothionein III (MT III) gene was synthesized with Escherichia coli preference codon usage and expressed in E. coli in glutathione-S-transferase (GST) fusion form. The recombinant MT III was released by proteinase Factor Xa digestion and purified with the yield of 2 mg/L culture, and its specific Cd2+ binding capability was confirmed. E. coli strain BL21(DE3), expressing MT III, showed metal tolerance between 0.1 and 0.5 mM Cd2+ and bacterial growth was inhibited at 1 mM Cd2+. MT III expressing E. coli strain showed binding discrimination between different metal ions in combination use, with the preference order of Cd2+ > Cu2+ > Zn2+. It absorbed different metal ions with relatively constant ratio and showed a cumulative absorption capability for mixed heavy metals. [ABSTRACT FROM AUTHOR]

Abstract: MicroRNAs (miRNAs) are a group of short (∼22nt) noncoding RNAs that specifically regulate cellular gene expression at the post-transcriptional level. miRNA precursors (pre-miRNAs), which are imperfect stem loop structures of ∼70nt, are processed into mature miRNAs by cellular RNases III. To date, hundreds of miRNAs and their corresponding targets have been reported in kinds of species. Although only a few of these miRNA/target pairs have been functionally verified, some do play important roles in regulating normal development and physiology. Several viruses (e.g. the Epstein-Barr virus and human herpesvirus Kaposi''s sarcoma-associated herpesvirus) has been reported to encode miRNAs. Here, we extend the analysis of miRNA-encoding potential to the Hepatitis B virus (HBV). Using computational approaches, we found that HBV putatively encodes only one candidate pre-miRNA. We then matched deduced mature miRNA sequence from this pre-miRNA against a database of 3′ untranslated sequences (UTR) from the human genome. Surprisingly, none of cellular transcripts could potentially be targeted by the viral miRNA (vmiRNA) sequence. However, one viral mRNA was found to be targeted by the vmiRNA when we searched the target from viral mRNAs. We propose that HBV has evolved to use vmiRNAs as a means to regulate its own gene expression for its benefit. [Copyright &y& Elsevier]

• Two novel genes were cloned and characterized from apricots (PaPG1 and PaPME1). • 1-MCP treatment delayed firmness reduction and softening in apricots. • 1-MCP treatment inhibited the ethylene production in apricots during cold storage. • 1-MCP treatment suppressed PaPG1 , PaPME1 gene expressions and PG, PME activities. • 1-MCP treatment maintained the fruit quality during shelf life in apricot fruit. Apricot softening is an important physiological process that influences fruit quality and postharvest life. Polygalacturonase (PG; EC 3.2.1.6.9) and pectin methylesterase (PME; EC 3.1.11) are two important cell wall hydrolases that have been widely studied during fruit softening. However, the roles of PG and PME genes in apricot softening remain unclear. In the present study, PaPG1 and PaPME1 from the apricot fruit were cloned and characterized. Moreover, the effects of 1-methylcyclopropene (1-MCP) treatment on firmness, ethylene production, PaPG1 and PaPME1 expression levels as well as PG and PME activities in apricots during storage at 4 ℃ were investigated, and the quality traits of apricot fruit during shelf life at 25 ℃ after cold storage were analyzed. Results showed that the application of 1-MCP significantly inhibited the decrease in fruit firmness as well as the increase in ethylene production, and markedly suppressed the expression levels of PaPG1 and PaPME1 and the increases in PG and PME activities of the apricots during cold storage. In addition, the 1-MCP treated apricots exhibited higher firmness, titratable acid (TA) content as well as lower ethylene production, respiration rate and weight loss compared to the control during shelf life at 25 ℃. These results suggested that 1-MCP treatment delayed the softening and ripening of the apricots during cold storage, and maintained better quality and consumer acceptability of the apricots during shelf life. PG and PME genes might play crucial roles in the development of apricot softening during cold storage. [ABSTRACT FROM AUTHOR]

• We propose BayesImpute, a novel statistical algorithm to impute scRNA-seq data. BayesImpute first identifies likely dropouts, and then only imputes these values, which preserves the true biological signal and reduces the introduction of unwanted bias during imputation. • Unlike other statistical imputation methods, the identification process of BayesImpute is straightforward and avoids parameter estimation, which increases its efficiency and user-friendliness in practice. In addition, BayesImpute takes advantage of cell-to-cell relationships and employs the Bayes approach to recover true biological signals, making the obtained estimations interpretable. • Using simulated and real scRNA-seq datasets, we demonstrate that BayesImpute can effectively identify dropouts, reduce the introduction of false positive signals, better recover the missing biological signals, and improve the reliability of some downstream analyses. More importantly, BayesImpute outperforms other statistical model-based methods in terms of computational running time, memory usage, and scalability. Single-cell RNA-sequencing (scRNA-seq) data suffer from a lot of zeros. Such dropout events impede the downstream data analyses. We propose BayesImpute to infer and impute dropouts from the scRNA-seq data. Using the expression rate and coefficient of variation of the genes within the cell subpopulation, BayesImpute first determines likely dropouts, and then constructs the posterior distribution for each gene and uses the posterior mean to impute dropout values. Some simulated and real experiments show that BayesImpute can effectively identify dropout events and reduce the introduction of false positive signals. Additionally, BayesImpute successfully recovers the true expression levels of missing values, restores the gene-to-gene and cell-to-cell correlation coefficient, and maintains the biological information in bulk RNA-seq data. Furthermore, BayesImpute boosts the clustering and visualization of cell subpopulations and improves the identification of differentially expressed genes. We further demonstrate that, in comparison to other statistical-based imputation methods, BayesImpute is scalable and fast with minimal memory usage. [ABSTRACT FROM AUTHOR]

Background: Many evidences have demonstrated that circRNAs (circular RNA) play important roles in controlling gene expression of human, mouse and nematode. More importantly, circRNAs are also involved in many diseases through fine tuning of post-transcriptional gene expression by sequestering the miRNAs which associate with diseases. Therefore, identifying the circRNA-disease associations is very appealing to comprehensively understand the mechanism, treatment and diagnose of diseases, yet challenging. As the complex mechanism between circRNAs and diseases, wet-lab experiments are expensive and time-consuming to discover novel circRNA-disease associations. Therefore, it is of dire need to employ the computational methods to discover novel circRNA-disease associations. Result: In this study, we develop a method (DWNN-RLS) to predict circRNA-disease associations based on Regularized Least Squares of Kronecker product kernel. The similarity of circRNAs is computed from the Gaussian Interaction Profile(GIP) based on known circRNA-disease associations. In addition, the similarity of diseases is integrated by the mean of GIP similarity and sematic similarity which is computed by the direct acyclic graph (DAG) representation of diseases. The kernels of circRNA-disease pairs are constructed from the Kronecker product of the kernels of circRNAs and diseases. DWNN (decreasing weight k-nearest neighbor) method is adopted to calculate the initial relational score for new circRNAs and diseases. The Kronecker product kernel based regularised least squares approach is used to predict new circRNA-disease associations. We adopt 5-fold cross validation (5CV), 10-fold cross validation (10CV) and leave one out cross validation (LOOCV) to assess the prediction performance of our method, and compare it with other six competing methods (RLS-avg, RLS-Kron, NetLapRLS, KATZ, NBI, WP). Conlusion: The experiment results show that DWNN-RLS reaches the AUC values of 0.8854, 0.9205 and 0.9701 in 5CV, 10CV and LOOCV, respectively, which illustrates that DWNN-RLS is superior to the competing methods RLS-avg, RLS-Kron, NetLapRLS, KATZ, NBI, WP. In addition, case studies also show that DWNN-RLS is an effective method to predict new circRNA-disease associations. [ABSTRACT FROM AUTHOR]

Each vertebrate species appears to have a unique timing mechanism for forming somites along the vertebral column, and the process in human remains poorly understood at the molecular level due to technical and ethical limitations. Here, we report the reconstitution of human segmentation clock by direct reprogramming. We first reprogrammed human urine epithelial cells to a presomitic mesoderm (PSM) state capable of long‐term self‐renewal and formation of somitoids with an anterior‐to‐posterior axis. By inserting the RNA reporter Pepper into HES7 and MESP2 loci of these iPSM cells, we show that both transcripts oscillate in the resulting somitoids at ~5 h/cycle. GFP‐tagged endogenous HES7 protein moves along the anterior‐to‐posterior axis during somitoid formation. The geo‐sequencing analysis further confirmed anterior‐to‐posterior polarity and revealed the localized expression of WNT, BMP, FGF, and RA signaling molecules and HOXA‐D family members. Our study demonstrates the direct reconstitution of human segmentation clock from somatic cells, which may allow future dissection of the mechanism and components of such a clock and aid regenerative medicine. Synopsis: Spatial patterning and temporal rhythmicity of gene expression define human embryogenesis during primitive streak stages but have been notoriously difficult to explore. This resource establishes a reprogramming culture system to mimic spatio‐temporal dynamics during somitogenesis and body axis formation, offering new insights into the signaling pathways involved. Direct reprogramming of human urine epithelial cells into presomitic mesoderm (PSM) cells recapitulates somitogenic differentiation and tissue segmentation.The Nodal pathway is required for urine‐induced PSM (UiPSM) self‐organization into somitoids and long‐term culture.UiPSM‐derived somitoids show oscillation of HES7 and MESP2 transcripts.UiPSM‐derived somitoids establish anterior–posterior polarity and regional expression of WNT, BMP, FGF, and RA signaling pathway components. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) has a strong genetic predisposition. However, its risk genes remain incompletely identified. We developed an Alzheimer's brain gene network-based approach to predict AD-associated genes by leveraging the functional pattern of known AD-associated genes. Our constructed network outperformed existing networks in predicting AD genes. We then systematically validated the predictions using independent genetic, transcriptomic, proteomic data, neuropathological and clinical data. First, top-ranked genes were enriched in AD-associated pathways. Second, using external gene expression data from the Mount Sinai Brain Bank study, we found that the top-ranked genes were significantly associated with neuropathological and clinical traits, including the Consortium to Establish a Registry for Alzheimer's Disease score, Braak stage score and clinical dementia rating. The analysis of Alzheimer's brain single-cell RNA-seq data revealed cell-type-specific association of predicted genes with early pathology of AD. Third, by interrogating proteomic data in the Religious Orders Study and Memory and Aging Project and Baltimore Longitudinal Study of Aging studies, we observed a significant association of protein expression level with cognitive function and AD clinical severity. The network, method and predictions could become a valuable resource to advance the identification of risk genes for AD. [ABSTRACT FROM AUTHOR]

Abstract: SALL4 is one of the master transcriptional factors that are crucial in maintaining the pluripotency of embryonic stem cells (ESCs). While the expression of SALL4 is normally restricted to ESCs and somatic stem cells, we found that it is aberrantly expressed in ALK-positive anaplastic large cell lymphoma (ALK+ ALCL), a type of lymphoid malignancy carrying a mature T-cell immunophenotype. shRNA knockdown of SALL4 in ALK+ ALCL cell lines resulted in apoptosis and cell-cycle arrest, and significantly decreased colony formation on soft agar. These changes correlated with the downregulation of several anti-apoptotic proteins and facilitators of cell-cycle progression. Based on the differential response to a SALL4 reporter construct, we were able to separate two distinct cell subsets in Karpas 299 (an ALK+ ALCL cell line), namely SALL4high and SALL4low. Importantly, the biological effects induced by SALL4 knock-down in Karpas 299 were restricted to the purified SALL4high cells, and this finding further supports the concept that SALL4 is biologically important in ALK+ ALCL. Lastly, the expression of SALL4 was not dependent on the nucleophosmin (NPM)-anaplastic lymphoma kinase (ALK)/STAT3 signaling axis, the key oncogenic driver in ALK+ ALCL. To conclude, for the first time, our study has revealed the oncogenic contributions of an ESC protein in the pathogenesis of ALK+ ALCL. [Copyright &y& Elsevier]

Abstract: The transcriptional factor Twist1 has been shown to play a key role in regulating epithelial mesenchymal transition, invasiveness and migratory properties in solid tumors. We found that Twist1 is aberrantly expressed in ALK-positive anaplastic large cell lymphoma (ALK+ALCL), a type of T-cell lymphoid malignancy. Using RT-PCR and Western blots, Twist1 was detectable in all 3 ALK+ALCL cell lines examined but absent in normal T-cells. By immunohistochemistry, Twist1 was detectable in all 10 cases of ALK+ALCL examined; benign lymphoid tissues were consistently negative. Twist1 expression in ALK+ALCL cells can be attributed to the NPM-ALK/STAT3 signaling axis, the key oncogenic driving force in this tumor type. Twist1 is biologically important in ALK+ALCL cells, as Twist1 knockdown resulted in a significant decrease in their invasiveness in an in-vitro assay. Further investigation revealed that this increase in invasiveness is linked to the activation of AKT and down-regulation of p66Shc, two signaling proteins known to be involved in NPM-ALK-mediated oncogenesis. Lastly, knockdown of Twist1 sensitizes ALK+ALCL cells to the growth inhibitory effect of PF-2341066 (Crizotinib®), an ALK inhibitor being used in clinical trials. In conclusion, Twist1 expression, owing to the abnormal NPM-ALK/STAT3 signaling, contributes to its invasiveness and decreased sensitivity to PF-2341066 in ALK+ALCL. [Copyright &y& Elsevier]

Background: With the development of the technology of single-cell sequence, revealing homogeneity and heterogeneity between cells has become a new area of computational systems biology research. However, the clustering of cell types becomes more complex with the mutual penetration between different types of cells and the instability of gene expression. One way of overcoming this problem is to group similar, related single cells together by the means of various clustering analysis methods. Although some methods such as spectral clustering can do well in the identification of cell types, they only consider the similarities between cells and ignore the influence of dissimilarities on clustering results. This methodology may limit the performance of most of the conventional clustering algorithms for the identification of clusters, it needs to develop special methods for high-dimensional sparse categorical data. Results: Inspired by the phenomenon that same type cells have similar gene expression patterns, but different types of cells evoke dissimilar gene expression patterns, we improve the existing spectral clustering method for clustering single-cell data that is based on both similarities and dissimilarities between cells. The method first measures the similarity/dissimilarity among cells, then constructs the incidence matrix by fusing similarity matrix with dissimilarity matrix, and, finally, uses the eigenvalues of the incidence matrix to perform dimensionality reduction and employs the K-means algorithm in the low dimensional space to achieve clustering. The proposed improved spectral clustering method is compared with the conventional spectral clustering method in recognizing cell types on several real single-cell RNA-seq datasets. Conclusions: In summary, we show that adding intercellular dissimilarity can effectively improve accuracy and achieve robustness and that improved spectral clustering method outperforms the traditional spectral clustering method in grouping cells. [ABSTRACT FROM AUTHOR]

Esophageal squamous cell carcinoma (ESCC) is one of the aggressive and lethal malignancies with an extremely poor prognosis. It is necessary to explore the molecular mechanisms of ESCC invasion. We utilized high-throughput mass spectrometry to analyze the proteomes and phosphorylation profiles of two ESCC cell lines with differing invasion capacities (HK vs TE10). Differentially expressed proteins and phosphorites were identified, followed by comprehensive bioinformatics analyses encompassing function and pathway enrichment, protein-protein interaction (PPI) network analysis, hub gene identification, co-expression analysis, kinase-substrate prediction, and drug-target network analysis. CCK-8 assay, transwell examination, wound-healing assay, and western blot was used to validate the effects of fostamatinib on ESCC cells proliferation, invasion, migration, and LYN expression. The Q4 cluster of differentially phosphorylated proteins was primarily associated with functions and pathways relevant to tumor metastasis. Phosphorylated hub proteins including ARHGAP35, CTNNA1, and SHC1 were identified through the analysis of PPI network, and their respective regulated kinases were predicted. Among the predicted kinases, LYN was validated to be associated with lymph node metastasis (N0 vs. N1–3) and prognosis in ESCC patients at mRNA levels using TGGA data and protein levels in ESCC tissues (p < 0.05). Validation experiments confirmed the inhibitory effects of fostamatinib on ESCC cells proliferation, migration, invasion, and LYN expression. Our multi-omics analysis offers deeper perspectives on ESCC invasiveness and unveils new phosphorylated hub proteins with their regulatory kinase. This study also suggests that fostamatinib may be a potential agent for treating ESCC. [Display omitted] [ABSTRACT FROM AUTHOR]

PBX3 (Pre-B-cell leukemia homeobox 3) had been considered to be a multifunctional oncogene which involved in tumor growth, invasion, and metastasis in leukemia and some solid tumors. However, the contribution of PBX3 to papillary thyroid carcinoma (PTC) remains unclear. In this study, we found that PBX3 expression was significantly upregulated in PTC tissues compared to adjacent normal tissues, and high levels of PBX3 were correlated with tumor size, lymphatic metastasis, TMN stage, and poor prognosis of PTC patients. Overexpression of PBX3 in PTC cell lines promoted cell proliferation. Consistently, knockdown of PBX3 by shRNA induced cell cycle arrest at G0/G1 phase, and inhibited angiogenesis and tumor growth in vitro and in vivo. Furthermore, PBX3 promoted PTC cell proliferation and angiogenesis through activation of AT1R/VEGFR2 pathway while overexpression of AT1R and treatment with VEGFA reversed PBX3-shRNA-induced decreased phosphorylation of VEGFR2 and its downstream (ERK1/2, AKT and Src). It demonstrated that PBX3 could be used as a potential prognostic biomarker and therapeutic target for PTC. [ABSTRACT FROM AUTHOR]

• PPI network was refined with gene expression and subcellular localization information. • The combination of topology properties and protein structure information was evaluated. • A new model with order statistics was proposed to get the final scores to rank the essential protein. Many computational methods have been proposed to predict essential proteins from protein-protein interaction (PPI) networks. However, it is still challenging to improve the prediction accuracy. In this study, we propose a new method, esPOS (essential proteins Predictor using Order Statistics) to predict essential proteins from PPI networks. Firstly, we refine the networks by using gene expression information and subcellular localization information. Secondly, we design some new features, which combine the protein predicted secondary structure with PPI network. We show that these new features are useful to predict essential proteins. Thirdly, we optimize these features by using a greedy method, and combine the optimized features by order statistic method. Our method achieves the prediction accuracy of 0.76–0.79 on two network datasets. The proposed method is available at https://sourceforge.net/projects/espos/ Image, graphical abstract [ABSTRACT FROM AUTHOR]

Motivation Reconstructing gene regulatory networks (GRNs) based on gene expression profiles is still an enormous challenge in systems biology. Random forest-based methods have been proved a kind of efficient methods to evaluate the importance of gene regulations. Nevertheless, the accuracy of traditional methods can be further improved. With time-series gene expression data, exploiting inherent time information and high order time lag are promising strategies to improve the power and accuracy of GRNs inference. Results In this study, we propose a scalable, flexible approach called BiXGBoost to reconstruct GRNs. BiXGBoost is a bidirectional-based method by considering both candidate regulatory genes and target genes for a specific gene. Moreover, BiXGBoost utilizes time information efficiently and integrates XGBoost to evaluate the feature importance. Randomization and regularization are also applied in BiXGBoost to address the over-fitting problem. The results on DREAM4 and Escherichia coli datasets show the good performance of BiXGBoost on different scale of networks. Availability and implementation Our Python implementation of BiXGBoost is available at https://github.com/zrq0123/BiXGBoost. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

CircR2Disease is a manually curated database, which provides a comprehensive resource for circRNA deregulation in various diseases. Increasing evidences have shown that circRNAs play critical roles in transcriptional, post-transcriptional and translational regulation. Therefore, the aberrant expression of circRNAs has been associated with a group of diseases. It is significant to develop a high-quality database to deposit the deregulated circRNAs in diseases. The current version of CircR2Disease contains 725 associations between 661 circRNAs and 100 diseases by reviewing existing literatures. Each entry in the CircR2Disease contains detailed information for the circRNA–disease relationship, including circRNA name, coordinates and gene symbol, disease name, expression patterns of circRNA, experimental techniques, a brief description of the circRNA–disease relationship, year of publication and the PubMed ID. CircR2Disease provides a user-friendly interface to browse, search and download as well as to submit novel disease-related circRNAs. CircR2Disease could be very beneficial for researches to investigate the mechanism of disease-related circRNAs and explore the appropriate algorithms for predicting novel associations. Database URL : http://bioinfo.snnu.edu.cn/CircR2Disease/ [ABSTRACT FROM AUTHOR]

Background: Essential proteins are necessary for the survival and development of cells. The identification of essential proteins can help to understand the minimal requirements for cellular life and it also plays an important role in the disease genes study and drug design. With the development of high-throughput techniques, a large amount of protein-protein interactions data is available to predict essential proteins at the network level. Hitherto, even though a number of essential protein discovery methods have been proposed, the prediction precision still needs to be improved. Methods: In this paper, we propose a new algorithm, improved Flower Pollination algorithm (FPA) for identifying Essential proteins, named FPE. Different from other existing essential protein discovery methods, we apply FPA which is a new intelligent algorithm imitating pollination behavior of flowering plants in nature to identify essential proteins. Analogous to flower pollination is to find optimal reproduction from the perspective of biological evolution, and the identification of essential proteins is to discover a candidate essential protein set by analyzing the corresponding relationships between FPA algorithm and the prediction of essential proteins, and redefining the positions of flowers and specific pollination process. Moreover, it has been proved that the integration of biological and topological properties can get improved precision for identifying essential proteins. Consequently, we develop a GSC measurement in order to judge the essentiality of proteins, which takes into account not only the Gene expression data, Subcellular localization and protein Complexes information, but also the network topology. Results: The experimental results show that FPE performs better than the state-of-the-art methods (DC, SC, IC, EC, LAC, NC, PeC, WDC, UDoNC and SON) in terms of the prediction precision, precision-recall curve and jackknife curve for identifying essential proteins and also has high stability. Conclusions: We confirm that FPE can be used to effectively identify essential proteins by the use of nature-inspired algorithm FPA and the combination of network topology with gene expression data, subcellular localization and protein complexes information. The experimental results have shown the superiority of FPE for the prediction of essential proteins. [ABSTRACT FROM AUTHOR]

Microglial activation plays a crucial role in the pathological processes of various retinal and optic nerve diseases. TNF-α is a pro-inflammatory cytokine that is rapidly upregulated and promotes retinal ganglion cells (RGCs) death after optic nerve injury. However, the cellular source of TNF-α after optic nerve injury remains unclear. Thus, we aimed to determine the changes of retinal microglial activation in a rat model of optic nerve transection (ONT) after transcorneal electrical stimulation (TES). Furthermore, we assessed TNF-α expression after ONT and evaluated the effects of TES on TNF-α production. Rats were divided into 2 control groups receiving a sham surgery procedure, 2 ONT+Sham TES groups, and 2 ONT+TES groups. The rats were sacrificed on day 7 or 14 after ONT. RGCs were retrogradely labelled by Fluorogold (FG) 7 days before ONT, one TES group and corresponding controls were stimulated on day 0, 4, and the second were stimulated on day 0, 4, 7, 10. Whole-mount immunohistofluorescence, quantification of RGCs and microglia, and western blot analysis were performed on day 7 and 14 after ONT. TES significantly increased RGCs survival on day 7 and 14 after ONT, which was accompanied by reduced microglia on day 7, but not 14. TNF-α was co-localized with ameboid microglia and significantly increased on day 7 and 14 after ONT. TES significantly reduced TNF-α production on day 7 and 14 after ONT. Our study demonstrated that TES promotes RGCs survival after ONT accompanied by reduced microglial activation and microglia-derived TNF-α production. [ABSTRACT FROM AUTHOR]

Essential proteins are indispensable for the survival of a living organism and play important roles in the emerging field of synthetic biology. Many computational methods have been proposed to identify essential proteins by using the topological features of interactome networks. However, most of these methods ignored intrinsic biological meaning of proteins. Researches show that essentiality is tied not only to the protein or gene itself, but also to the molecular modules to which that protein belongs. The results of this study reveal the modularity of essential proteins. On the other hand, essential proteins are more evolutionarily conserved than nonessential proteins and frequently bind each other. That is to say, conservatism is another important feature of essential proteins. Multiple networks are constructed by integrating protein-protein interaction (PPI) networks, time course gene expression data and protein domain information. Based on these networks, a new essential protein identification method is proposed based on a combination of modularity and conservatism of proteins. Experimental results show that the proposed method outperforms other essential protein identification methods in terms of a number essential protein out of top ranked candidates. [ABSTRACT FROM AUTHOR]

• SA treatment effectively delayed firmness reduction and softening in apricots. • SA treatment significantly inhibited the ethylene biosynthesis of apricots. • SA treatment suppressed PaPG1 and PaPME1 gene expressions in apricots. • SA treatment reduces cellulose, β -glucosidase, PG, PME activities. • SA treatment delayed the degradation of pectin and protected cell wall structure. Apricots softening senescence is a complex metabolic network, and these metabolic pathways coordinate with each other to make aging irreversible. To identify and implement treatments to delay ripening senescence in apricots, the effects of salicylic acid (SA) treatment on ethylene biosynthesis and cell wall degradation were investigated during 35 days of storage at 4 °C and 90%-95% relative humidity. In contrast with control, SA treatment suppressed ethylene production due to inhibited ACC synthase (ACS) and ACC oxidase (ACO) activities and reduced 1-aminocyclopropane-1-carboxylic acid (ACC) content. Furthermore, the decreases in fruit firmness, contents of CDTA-soluble pectin (CSP), Na 2 CO 3 -soluble pectin (NSP), hemicellulose as well as cellulose, and the increase in water-soluble pectin (WSP) of the apricots could be delayed by SA treatment. Enzyme activities of cellulase (EC 3.2.1.4), β -glucosidase (EC 3.2.1.21), polygalacturonase (PG; EC 3.2.1.15), pectin methylesterase (PME; EC 3.1.1.11) as well as PaPG1 and PaPME1 gene expressions were suppressed strongly by SA treatment and these two genes were closely correlated with fruit softening. In addition, transmission electron microscopy (TEM) images demonstrated that the softening process of SA-treated apricots could be delayed efficiently and preventing structural breakdown. These results suggest that cell wall degrading enzyme activities are regulated by ethylene, and SA treatment mitigated apricots softening by inhibiting ethylene biosynthesis and decreasing cell degrading enzyme activities. [ABSTRACT FROM AUTHOR]

Bombyx mori presents several types of egg color mutations, all of which have been extensively discussed in sericulture. While the red egg mutation has been previously observed, lethal red-egg mutants have not been reported. In the present work, the red egg mutant Fuyin-lre (Fuyin-lethal red egg) was discovered from the Fuyin germplasm resource of B. mori. This mutant features red-colored eggs and embryonic lethality. Genetic analysis showed that Fuyin-lre follows recessive inheritance, with the red egg gene re governing the egg color, and the embryonic lethality of Fuyin-lre may be caused by mutations of other genes closely linked to re. Digital gene expression (DGE) was employed to compare the transcription profiles of Fuyin and Fuyin-lre eggs after 24 and 48 h of incubation. A total of 48 differentially expressed genes followed the same expression patterns in both groups at both time points (FDR < 0.01 and log 2 Ratio ≥ 1). Further analyses indicated that 8 out of the 48 genes (including re) were closely linked to re. These 8 genes were highly expressed in wild-type Fuyin and the red egg mutant re but showed nearly absent expression in Fuyin-lre. Sequencing of the re gene confirmed that the re gene itself does not induce embryonic lethality, and structure analysis showed that the structural variation of the region where the 8 genes were located may be associated with the embryonic lethality of Fuyin-lre. The present work provides a good foundation for future studies on the mechanism of embryonic lethality and embryonic development in Fuyin-lre. [ABSTRACT FROM AUTHOR]

As genes with similar functions are closely related, cluster analysis becomes an important tool to understand and predicts gene functions (patterns) from gene expression profiles. In many situations, each gene expression profile only contains a few data points. Directly applying traditional clustering algorithms to such short gene expression profiles cannot obtain biological meaningful patterns. In this paper, we propose a novel method to discover biologically meaningful patterns by clustering short time-series gene expression profiles with integrating protein–protein interaction (PPI) data. Numerical experiments are conducted on two sets of Arabidopsis thaliana short time-series gene expression profiles, with treatments of cold stress and drought stress, respectively. The proposed method can effectively assign genes belonging to target functional clusters (patterns), in terms of having small p-value of GO term ‘response to cold’ ( GO:0009409 ) in dataset one, and small p-value of GO term ‘response to water deprivation’ ( GO:0009414 ) in dataset two than those from an existing clustering algorithm (namely STEM) for short time-series gene expression profiles. Additionally, our proposed method is able to identify higher percentage of stress-related genes and un-annotated genes in resultant cluster than STEM for both datasets; which does not only improve gene clustering effectiveness, but also contribute to functional prediction of un-annotated genes. [ABSTRACT FROM AUTHOR]

Liver X receptors (LXRs) have been recognized as a promising therapeutic target for atherosclerosis; however, their role in insulin sensitivity is controversial. Adiponectin plays a unique role in maintaining insulin sensitivity. Currently, no systematic experiments elucidating the role of LXR activation in insulin function based on adiponectin signaling have been reported. Here, we investigated the role of LXR activation in insulin resistance based on adiponectin signaling, and possible mechanisms. C57BL/6 mice maintained on a regular chow received the LXR agonist, T0901317 (30 mg/kg.d) for 3 weeks by intraperitoneal injection, and differentiated 3T3-L1 adipocytes were treated with T0901317 or GW3965. T0901317 treatment induced significant insulin resistance in C57BL/6 mice. It decreased adiponectin gene transcription in epididymal fat, as well as serum adiponectin levels. Activity of AMPK, a key mediator of adiponectin signaling, was also decreased, resulting in decreased Glut-4 membrane translocation in epididymal fat. In contrast, adiponectin activity was not changed in the liver of T0901317 treated mice. In vitro, both T0901317 and GW3965 decreased adiponectin expression in adipocytes in a dose-dependent manner, an effect which was diminished by LXRα silencing. ChIP-qPCR studies demonstrated that T0901317 decreased the binding of PPARγ to the PPAR-responsive element (PPRE) of the adiponectin promoter in a dose-dependent manner. Furthermore, T0901317 exerted an antagonistic effect on the expression of adiponectin in adipocytes co-treated with 3 µM Pioglitazone. In luciferase reporter gene assays, T0901317 dose-dependently inhibited PPRE-Luc activity in HEK293 cells co-transfected with LXRα and PPARγ. These results suggest that LXR activation induces insulin resistance with decreased adiponectin signaling in epididymal fat, probably due to negative regulation of PPARγ signaling. These findings indicate that the potential of LXR activation as a therapeutic target for atherosclerosis may be limited by the possibility of exacerbating insulin resistance-related disease. [ABSTRACT FROM AUTHOR]

Gene regulation change has long been recognized as an important mechanism for phenotypic evolution. We used the evolution of yeast aerobic fermentation as a model to explore how gene regulation has evolved and how this process has contributed to phenotypic evolution and adaptation. Most eukaryotes fully oxidize glucose to CO2 and H2O in mitochondria to maximize energy yield, whereas some yeasts, such as Saccharomyces cerevisiae and its relatives, predominantly ferment glucose into ethanol even in the presence of oxygen, a phenomenon known as aerobic fermentation. We examined the genome-wide gene expression levels among 12 different yeasts and found that a group of genes involved in the mitochondrial respiration process showed the largest reduction in gene expression level during the evolution of aerobic fermentation. Our analysis revealed that the downregulation of these genes was significantly associated with massive loss of binding motifs of Cbf1p in the fermentative yeasts. Our experimental assays confirmed the binding of Cbf1p to the predicted motif and the activator role of Cbf1p. In summary, our study laid a foundation to unravel the long-time mystery about the genetic basis of evolution of aerobic fermentation, providing new insights into understanding the role of cis-regulatory changes in phenotypic evolution. [ABSTRACT FROM PUBLISHER]

TGFβ1 is a key mediator in the progress of diabetic nephropathy. Proteoglycan II (decorin) ,a natural inhibitor of TGFβ1, can down-regulate TGFβ1 expression. In the present study, a recombinant adenovirus expressing decorin (AD-DCN) was used to investigate the effects of decorin overexpression on kidney of STZ-induced diabetic rats. Fouty eight Sprague-Dawley rats were randomly divided into 4 groups: normal control rats (group C), STZ-induced diabetic rats (group D, induced with 60mg/kg STZ), diabetic rats treated with AD- DCN (group P), and diabetic rats treated with recombinant adenovirus vector of LacZ gene (group L, used as transfected control). Recombinant adenovirus (0.6ml, 1x10[sup 9]/ml) transfected SD rats by intraperitoneal injection every 4 weeks from the 4th week after STZ-induced diabetes. The expression of decorin ,TGFβ1 and collagen IV mRNA in the renal cortex was examined by PCR at the 10th, the 12th, the 16th week after diabetic model completed. Kidney hypertrophy index [KHI,expressed by the ratio of kidney weight (g)/body weight(kg)], blood glucose level and urinary protein excretion (UPE, expressed as the ratio of urinary protein/urinary creatinine) were also determined. KHI of group D, L and P were respectively increased 1.7∼1.8, 1.9∼2.1, 1.5∼1.6 folds compared with that of group C (P <0.05). AD-DCN had no significant effect on KHI. Compared with group C, rats of group D and group L had 3.1∼3.5, 2.8∼4.6 folds increasing of UPE (P<0.05). There were no difference of UPE between group D and group L, indicating that adenovirus itself have no effect on UPE. Decorin gene transfection decreased 59% UPE of group D at the 16th week (P<0.05).The results of PCR showed that rats of group D and group L had higher expression of decorin, TGFβ1 and collagen IV in renal cortex than group C[decorin: group D1.6∼2.2 folds, group L1.7∼2.2 folds; TGFβ1: group D 1.8∼2.4 folds, group L1.7∼2.2; collagen IV: group D1.7 ∼ 4.5 folds, group L 1.7∼4.9folds; (P<0.01)]. Group P could express more decorin mRNA (1.1∼1.3 folds) than group D. Decorin overexpression blunted the expression of TGFβ1 (0.65 folds group D). Meanwhile, collagen IV mRNA levels in group P were prominently inhibited [0.3∼0.6 folds group D (P<0.01)] and reached to near normal level. Decorin gene transfection mediated by a recombinant adenovirus has anti-renal fibrosis and proteinuric effect in STZ-induced diabetic rats. The renal protective effect of decorin is at least partially due to the downregulation of TGFβ1 expression. [ABSTRACT FROM AUTHOR]

Summary Endothelial progenitor cells (EPCs) play an important role in repairing endothelial injury. Aging is associated with EPC dysfunction. Physical exercise has a beneficial impact on EPC activity. However, whether physical exercise can enhance the endothelial repair capacity of EPCs in healthy men with aging is not clear. Here, we investigated the effects of physical exercise on reendothelialization capacity and CXC chemokine receptor four (CXCR4) signaling in human EPCs. Before and after 12-week exercise, EPCs were isolated from elderly and young men. In vitro function and in vivo reendothelialization capacity of EPCs in a mouse model of carotid artery injury were measured. The expression of CXCR4 and its downstream signaling target Janus kinase-2 (JAK-2) were determined. Before exercise, in vitro function and in vivo reendothelialization capacity of EPCs were significantly reduced in elderly men compared with young men. After exercise intervention, in vitro function and in vivo reendothelialization capacity of EPCs from elderly men were markedly enhanced. Physical exercise increased a higher CXCR4 protein expression and higher JAK-2 phosphorylation levels of EPCs. The augmentation in reendothelialization capacity of EPCs was closely correlated with the upregulation of CXCR4/JAK-2 signaling and improvement of endothelial function. This study demonstrates for the first time that physical exercise attenuates age-associated reduction in endothelium-reparative capacity of EPCs by increasing CXCR4/JAK-2 signaling. Our findings provide insight into the novel mechanisms of physical exercise as a lifestyle intervention strategy to promote vascular health in aging population. [ABSTRACT FROM AUTHOR]