More than 30 prostate cancer (PCa) risk-associated loci have been identified in populations of European descent by genome-wide association studies (GWAS). We hypothesized that a subset of these loci may be associated with PCa risk in Chinese men. To test this hypothesis, 33 single nucleotide polymorphisms (SNPs), one each from the 33 independent PCa risk-associated loci reported in populations of European descent, were investigated for their associations with PCa risk in a case-control study of Chinese men (1,108 cases and 1,525 controls). We found that 11 of the 33 SNPs were significantly associated with PCa risk in Chinese men (P < 0.05). The reported risk alleles were associated with increased risk for PCa, with allelic odds ratios ranging from 1.12 to 1.44. The most significant locus was located on 8q24 Region 2 (rs16901979, P = 5.14×10−9) with a genome-wide significance (P < 10−8), and three loci reached the Bonferroni correction significance level (P < 1.52×10−3), including 8q24 Region 1 (rs1447295, P = 7.04×10−6), 8q24 Region 5 (rs10086908, P = 9.24×10−4), and 8p21 (rs1512268, P = 9.39×10−4). Our results suggest that a subset of the PCa risk-associated SNPs discovered by GWAS among men of European descent is also associated with PCa risk in Chinese men. This finding provides evidence of ethnic differences and similarity in genetic susceptibility to PCa. GWAS in Chinese men are needed to identify Chinese-specific PCa risk-associated SNPs.

Background

Cooperia oncophora and Ostertagia ostertagi are among the most important gastrointestinal nematodes of cattle worldwide. The economic losses caused by these parasites are on the order of hundreds of millions of dollars per year. Conventional treatment of these parasites is through anthelmintic drugs; however, as resistance to anthelmintics increases, overall effectiveness has begun decreasing. New methods of control and alternative drug targets are necessary. In-depth analysis of transcriptomic data can help provide these targets.

Results

The assembly of 8.7 million and 11 million sequences from C. oncophora and O. ostertagi, respectively, resulted in 29,900 and 34,792 transcripts. Among these, 69% and 73% of the predicted peptides encoded by C. oncophora and O. ostertagi had homologues in other nematodes. Approximately 21% and 24% were constitutively expressed in both species, respectively; however, the numbers of transcripts that were stage specific were much smaller (~1% of the transcripts expressed in a stage). Approximately 21% of the transcripts in C. oncophora and 22% in O. ostertagi were up-regulated in a particular stage. Functional molecular signatures were detected for 46% and 35% of the transcripts in C. oncophora and O. ostertagi, respectively. More in-depth examinations of the most prevalent domains led to knowledge of gene expression changes between the free-living (egg, L1, L2 and L3 sheathed) and parasitic (L3 exsheathed, L4, and adult) stages. Domains previously implicated in growth and development such as chromo domains and the MADF domain tended to dominate in the free-living stages. In contrast, domains potentially involved in feeding such as the zinc finger and CAP domains dominated in the parasitic stages. Pathway analyses showed significant associations between life-cycle stages and peptides involved in energy metabolism in O. ostertagi whereas metabolism of cofactors and vitamins were specifically up-regulated in the parasitic stages of C. oncophora. Substantial differences were observed also between Gene Ontology terms associated with free-living and parasitic stages.

Conclusions

This study characterized transcriptomes from multiple life stages from both C. oncophora and O. ostertagi. These data represent an important resource for studying these parasites. The results of this study show distinct differences in the genes involved in the free-living and parasitic life cycle stages. The data produced will enable better annotation of the upcoming genome sequences and will allow future comparative analyses of the biology, evolution and adaptation to parasitism in nematodes.

Objective

Although the association between alanine aminotransferase (ALT) levels and risk of type 2 diabetes is well-studied, the effects of slightly increased ALT levels within the normal range on the temporal normal glucose profile remains poorly understood.

Methods

A total of 322 Chinese subjects without impaired glucose tolerance or previous diagnoses of diabetes were recruited for study from 10 hospitals in urban areas across China. All subjects wore a continuous glucose monitoring (CGM) system for three consecutive days. The diurnal (06∶00–20∶00) and nocturnal (20∶00–06∶00) mean blood glucose (MBG) levels were calculated. Subjects were stratified by ALT quartile level and correlation analyses were performed.

Results

The median ALT level was 17 IU/L, and subjects with ALT ≥17 IU/L had higher nocturnal MBG level than those with ALT <17 IU/L (P<0.05). Nocturnal MBG was positively correlated with ALT levels (Pearson correlation analysis: r = 0.187, P = 0.001), and the correlation remained significant after correction for the homeostatic model assessment of insulin resistance index (HOMA-IR) (r = 0.105, P = 0.041). No correlations were found between diurnal MBG and ALT, and nocturnal or diurnal MBG and aspartate aminotransferase or gamma-glutamyltransferase (all, P>0.05). Multivariate stepwise regression analysis of elevated nocturnal MBG identified increased HOMA-IR, elevated ALT levels, and decreased homeostatic model assessment of ß-cell function as independent factors (all, P<0.05).

Conclusions

Mildly elevated ALT levels, within the normal range, are associated with unfavorable nocturnal glucose profiles in Chinese subjects with normal glucose regulation.

A recent genome-wide association study has identified five new genetic variants for prostate cancer susceptibility in a Japanese population, but it is unknown whether these newly identified variants are associated with prostate cancer risk in other populations, including Chinese men. We genotyped these five variants in a case–control study of 1524 patients diagnosed with prostate cancer and 2169 control subjects from the Chinese Consortium for Prostate Cancer Genetics (ChinaPCa). We found that three of the five genetic variants were associated with prostate cancer risk (P = 4.33 × 10−8 for rs12653946 at 5p15, 4.43 × 10−5 for rs339331 at 6q22 and 8.42 × 10−4 for rs9600079 at 13q22, respectively). A cumulative effect was observed in a dose-dependent manner with increasing numbers of risk variant alleles (Ptrend = 2.58 × 10−13), and men with 5–6 risk alleles had a 2-fold higher risk of prostate cancer than men with 0–2 risk alleles (odds ratio = 2.26, 95% confidence interval = 1.78–2.87). Furthermore, rs339331 T allele was significantly associated with RFX6 and GPRC6A higher messenger RNA expression, compared with the C allele. However, none of the variants was associated with clinical stage, Gleason score or family history. These results provide further evidence that the risk loci identified in Japanese men also contribute to prostate cancer susceptibility in Chinese men.

Background

Few data are available regarding the epidemiology of invasive aspergillosis (IA) in ICU patients. The aim of this study was to examine epidemiology and economic outcomes (length of stay, hospital costs) among ICU patients with IA who lack traditional risk factors for IA, such as cancer, transplants, neutropenia or HIV infection.

Methods

Retrospective cohort study using Premier Inc. Perspective™ US administrative hospital database (2005–2008). Adults with ICU stays and aspergillosis (ICD-9 117.3 plus 484.6) who received initial antifungal therapy (AF) in the ICU were included. Patients with traditional risk factors (cancer, transplant, neutropenia, HIV/AIDS) were excluded. The relationship of antifungal therapy and co-morbidities to economic outcomes were examined using Generalized linear models.

Results

From 6,424 aspergillosis patients in the database, 412 (6.4%) ICU patients with IA were identified. Mean age was 63.9 years and 53% were male. Frequent co-morbidities included steroid use (77%), acute respiratory failure (76%) and acute renal failure (41%). In-hospital mortality was 46%. The most frequently used AF was voriconazole (71% received at least once). Mean length of stay (LOS) was 26.9 days and mean total hospital cost was $76,235. Each 1 day lag before initiating AF therapy was associated with 1.28 days longer hospital stay and 3.5% increase in costs (p < 0.0001 for both).

Conclusions

Invasive aspergillosis in ICU patients is associated with high mortality and hospital costs. Antifungal timing impacts economic outcomes. These findings underscore the importance of timely diagnosis, appropriate treatment, and consideration of Aspergillus as a potential etiology in ICU patients.

A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into -values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx.

Abstract

As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.

Reviewers

This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.

EuPathDB (http://eupathdb.org) resources include 11 databases supporting eukaryotic pathogen genomic and functional genomic data, isolate data and phylogenomics. EuPathDB resources are built using the same infrastructure and provide a sophisticated search strategy system enabling complex interrogations of underlying data. Recent advances in EuPathDB resources include the design and implementation of a new data loading workflow, a new database supporting Piroplasmida (i.e. Babesia and Theileria), the addition of large amounts of new data and data types and the incorporation of new analysis tools. New data include genome sequences and annotation, strand-specific RNA-seq data, splice junction predictions (based on RNA-seq), phosphoproteomic data, high-throughput phenotyping data, single nucleotide polymorphism data based on high-throughput sequencing (HTS) and expression quantitative trait loci data. New analysis tools enable users to search for DNA motifs and define genes based on their genomic colocation, view results from searches graphically (i.e. genes mapped to chromosomes or isolates displayed on a map) and analyze data from columns in result tables (word cloud and histogram summaries of column content). The manuscript herein describes updates to EuPathDB since the previous report published in NAR in 2010.

Background

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.

Results

To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.

Conclusion

The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Background

The fern genus Dryopteris (Dryopteridaceae) is among the most common and species rich fern genera in temperate forests in the northern hemisphere containing 225–300 species worldwide. The circumscription of Dryopteris has been controversial and various related genera have, over the time, been included in and excluded from Dryopteris. The infrageneric phylogeny has largely remained unclear, and the placement of the majority of the supraspecific taxa of Dryopteris has never been tested using molecular data.

Results

In this study, DNA sequences of four plastid loci (rbcL gene, rps4-trnS spacer, trnL intron, trnL-F spacer) were used to reconstruct the phylogeny of Dryopteris. A total of 122 accessions are sampled in our analysis and they represent 100 species of the expanded Dryopteris including Acrophorus, Acrorumohra, Diacalpe, Dryopsis, Nothoperanema, and Peranema. All four subgenera and 19 sections currently recognized in Dryopteris s.s. are included. One species each of Arachniodes, Leptorumohra, and Lithostegia of Dryopteridaceae are used as outgroups. Our study confirms the paraphyly of Dryopteris and provides the first strong molecular evidence on the monophyly of Acrophorus, Diacalpe, Dryopsis, Nothoperanema, and Peranema. However, all these monophyletic groups together with the paraphyletic Acrorumohra are suggested to be merged into Dryopteris based on both molecular and morphological evidence. Our analysis identified 13 well-supported monophyletic groups. Each of the 13 clades is additionally supported by morphological synapomophies and is inferred to represent a major evolutionary lineage in Dryopteris. In contrast, monophyly of the four subgenera and 15 out of 19 sections currently recognized in Dryopteris s.s is not supported by plastid data.

Conclusions

The genera, Acrophorus, Acrorumohra, Diacalpe, Dryopsis, Nothoperanema, and Peranema, should all be merged into Dryopteris. Most species of these genera share a short rhizome and catadromic arrangement of frond segments, unlike the sister genus of Dryopteris s.l., Arachniodes, which has anadromic arrangement of frond segments. The non-monophyly of the 19 out of the 21 supraspecific taxa (sections, subgenera) in Dryopteris strongly suggests that the current taxonomy of this genus is in need of revision. The disagreement between the previous taxonomy and molecular results in Dryopteris may be due partly to interspecific hybridization and polyplodization. More morphological studies and molecular data, especially from the nuclear genome, are needed to thoroughly elucidate the evolutionary history of Dryopteris. The 13 well-supported clades identified based on our data represent 13 major evolutionary lineages in Dryopteris that are also supported by morphological synapomophies.

Haploinsufficiency for GATA2 causes human immunodeficiency syndromes characterized by mycobacterial infection, myelodysplasia, lymphedema, or aplastic anemia that progress to myeloid leukemia. GATA2 encodes a master regulator of hematopoiesis that is also linked to endothelial biology. Though the disease-causing mutations commonly occur in the GATA-2 DNA binding domain, we identified a patient with mycobacterial infection and myelodysplasia who had an uncharacterized heterozygous deletion in a GATA2 cis-element consisting of an E-box and a GATA motif. Targeted deletion of the equivalent murine element to yield homozygous mutant mice revealed embryonic lethality later than occurred with global Gata2 knockout, hematopoietic stem/progenitor cell depletion, and impaired vascular integrity. Heterozygous mutant mice were viable, but embryos exhibited deficits in definitive, but not primitive, hematopoietic stem/progenitor activity and reduced expression of Gata2 and its target genes. Mechanistic analysis revealed disruption of the endothelial cell transcriptome and loss of vascular integrity. Thus, the composite element disrupted in a human immunodeficiency is essential for establishment of the murine hematopoietic stem/progenitor cell compartment in the fetal liver and for essential vascular processes.

Motivation: Burgeoning sequencing technologies have generated massive amounts of genomic and proteomic data. Annotating the functions of proteins identified in this data has become a big and crucial problem. Various computational methods have been developed to infer the protein functions based on either the sequences or domains of proteins. The existing methods, however, ignore the recurrence and the order of the protein domains in this function inference.

Results: We developed two new methods to infer protein functions based on protein domain recurrence and domain order. Our first method, DRDO, calculates the posterior probability of the Gene Ontology terms based on domain recurrence and domain order information, whereas our second method, DRDO-NB, relies on the naïve Bayes methodology using the same domain architecture information. Our large-scale benchmark comparisons show strong improvements in the accuracy of the protein function inference achieved by our new methods, demonstrating that domain recurrence and order can provide important information for inference of protein functions.

Availability: The new models are provided as open source programs at http://sfb.kaust.edu.sa/Pages/Software.aspx.

Contact: dkihara@cs.purdue.edu, xin.gao@kaust.edu.sa

Supplementary information: Supplementary data are available at Bioinformatics Online.

OrthoMCL is an algorithm for grouping proteins into ortholog groups based on their sequence similarity. OrthoMCL-DB is a public database that allows users to browse and view ortholog groups that were pre-computed using the OrthoMCL algorithm. Version 4 of this database contained 116,536 ortholog groups clustered from 1,270,853 proteins obtained from 88 eukaryotic genomes, 16 archaeal genomes and 34 bacterial genomes. Future versions of OrthoMCL-DB will include more proteomes as more genomes are sequenced. Here, we describe how you can group your proteins of interest into ortholog clusters using two different means provided by the OrthoMCL system. The OrthoMCL-DB website has a tool for uploading and grouping a set of protein sequences, typically representing a proteome. This method maps the uploaded proteins to existing groups in OrthoMCL-DB. Alternatively, if you have proteins from a set of genomes that need to be grouped, you can download, install and run the standalone OrthoMCL software.

Objective

This study aimed to express a fusion protein of diphtheria toxin and human B cell-activating factor (DT388sBAFF) in Escherichia coli (E. coli) and investigate its activity in human B-lineage acute lymphoblastic leukemia 1 cells (BALL-1).

Methods

A fragment of DT388sBAFF fusion gene was separated from plasmid pUC57-DT388sBAFF digested with Nde I and Xho I, and inserted into the expression vector pcold II digested with the same enzymes. Recombinants were screened by the colony polymerase chain reaction (PCR) and restriction map. The recombinant expression vector was transformed into BL21 and its expression was induced by isopropyl β-D-1-thiogalactopyranoside (IPTG). The recombinant protein was identified by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blot, and then purified by Ni2+-NTA affinity chromatography. The expression level of B cell-activating factor receptor (BAFF-R) on BALL-1 cells was assessed by real-time PCR. The receptor binding capacity of recombinant protein was determined by cell fluorescent assay. The specific cytotoxicity of recombinant protein on BALL-1 cells was detected by 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) assay.

Results

The expression level of recombinant protein was 50% of total bacterial proteins in E. coli, and the recombinant protein could bind to BAFF-R-positive BALL-1 cells and thereby produce a cytotoxic effect on the cells.

Conclusion

The fusion protein expression vector DT388sBAFF was successfully constructed and the recombinant protein with selective cytotoxicity against BALL-1 cells was obtained, providing foundation for further study of the therapy of human B-lineage acute lymphoblastic leukemia.

Under the conditions of transfer hydrogenation employing a cyclometallated iridium catalyst (R)-I derived from [Ir(cod)Cl]2, allyl acetate, 4-cyano-3-nitrobenzoic acid and the chiral phosphine ligand (R)-SEGPHOS, α-methyl allyl acetate engages 1,3-propanediol 1a and 2-methyl-1,3-propanediol 1b in double carbonyl crotylation from the alcohol oxidation level to deliver the C2-symmetric and pseudo-C2-symmetric stereopolyads 2a and 3a, respectively, with exceptional control of anti-diastereo- and enantioselectivity. Notably, the polypropionate stereopentad 3a is formed predominantly as 1 of 16 possible stereoisomers. Desymmetrization of polypropionate stereopentad 3a is readily achieved upon iodoetherification to form pyran 4. Direct generation of polypropionate stereopentad 3a enables a dramatically simplified approach to previously prepared polypropionate substructures, as demonstrated by the synthesis of C19–C27 of rifamycin S (8 steps, originally prepared in 26 steps) and C19–C25 of scytophycin C (8 steps, originally prepared in 15 steps). The present transfer hydrogenative protocol represents an alternative to chiral auxiliaries, chiral reagents and premetallated nucleophiles in polyketide construction.

The precise three-dimensional (3-D) segmentation of cerebral vessels from magnetic resonance angiography (MRA) images is essential for the detection of cerebrovascular diseases (e.g., occlusion, aneurysm). The complex 3-D structure of cerebral vessels and the low contrast of thin vessels in MRA images make precise segmentation difficult. We present a fast, fully automatic segmentation algorithm based on statistical model analysis and improved curve evolution for extracting the 3-D cerebral vessels from a time-of-flight (TOF) MRA dataset. Cerebral vessels and other tissue (brain tissue, CSF, and bone) in TOF MRA dataset are modeled by Gaussian distribution and combination of Rayleigh with several Gaussian distributions separately. The region distribution combined with gradient information is used in edge-strength of curve evolution as one novel mode. This edge-strength function is able to determine the boundary of thin vessels with low contrast around brain tissue accurately and robustly. Moreover, a fast level set method is developed to implement the curve evolution to assure high efficiency of the cerebrovascular segmentation. Quantitative comparisons with 10 sets of manual segmentation results showed that the average volume sensitivity, the average branch sensitivity, and average mean absolute distance error are 93.6%, 95.98%, and 0.333 mm, respectively. By applying the algorithm to 200 clinical datasets from three hospitals, it is demonstrated that the proposed algorithm can provide good quality segmentation capable of extracting a vessel with a one-voxel diameter in less than 2 min. Its accuracy and speed make this novel algorithm more suitable for a clinical computer-aided diagnosis system.

Phosphoinositides play important roles in eukaryotic cells, although they constitute a minor fraction of total cellular lipids. Specific kinases and phosphatases function on the regulation of phosphoinositide levels. Phosphatidylinositol 3-phosphate (PtdIns3P), a molecule of phosphoinositides regulates multiple aspects of plant growth and development. In this article, we introduce and discuss the kinases and phosphatases involved in PtdIns3P metabolism and their roles in pollen development and pollen tube growth in Arabidopsis.

Background:

We designed dual-functional nanoparticles for in vivo application using a modified electrostatic and covalent layer-by-layer assembly strategy to address the challenge of assessment and treatment of hormone-refractory prostate cancer.

Methods:

Core-shell nanoparticles were formulated by integrating three distinct functional components, ie, a core constituted by poly(D,L-lactic-co-glycolic acid), docetaxel, and hydrophobic superparamagnetic iron oxide nanocrystals (SPIONs), a multilayer shell formed by poly(allylamine hydrochloride) and two different sized poly(ethylene glycol) molecules, and a single-chain prostate stem cell antigen antibody conjugated to the nanoparticle surface for targeted delivery.

Results:

Drug release profiles indicated that the dual-function nanoparticles had a sustained release pattern over 764 hours, and SPIONs could facilitate the controlled release of the drug in vitro. The nanoparticles showed increased antitumor efficiency and enhanced magnetic resonance imaging in vitro through targeted delivery of docetaxel and SPIONs to PC3M cells. Moreover, in nude mice bearing PC3M xenografts, the nanoparticles provided MRI negative contrast enhancement, as well as halting and even reversing tumor growth during the 76-day study duration, and without significant systemic toxicity. The lifespan of the mice treated with these targeted dual-function nanoparticles was significantly increased (Chi-square = 22.514, P < 0.0001).

Conclusion:

This dual-function nanomedical platform may be a promising candidate for tumor imaging and targeted delivery of chemotherapeutic agents in vivo.

Background

The study was undertaken to examine the effects of berberine (BBR) on serum homocysteine, lipids and the aortic lesion in Sprague–Dawley (SD) rats fed with a long-term high-fat diet (HFD).

Methods

Healthy male SD rats weighing 190-210 g received randomly standard diet or a high-fat diet for 24 weeks. After 8 weeks of feeding, rats fed with HFD were randomized to receive berberine (200 mg · kg-1· day-1) or vehicle by gavage for 16 weeks. After overnight fasting, all rats were sacrificed and total blood samples were also collected for determinant of fasting serum homocysteine (Hcy), total cholesterol (TC) and low density lipoprotein cholesterol (LDL-c) levels. The aorta was stained with hematoxylin and eosin (HE) and Sudan Ш to evaluate aortic lesion. The livers were dissected out and snap-frozen in liquid nitrogen for hepatic TC content and molecular analysis. 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMGR), Lipoprotein receptors and apolipoproteins gene expression in the liver were determined by real-time PCR.

Results

Intragastrical administration with berberine for 16 weeks lowered serum Hcy in rats fed with a high-fat diet. In parallel, it also decreased body weight and improved serum TC and LDL-c. Berberine also tended to decrease hepatic cholesterol. Consistently, berberine also upregulated LDL receptor (LDLR) mRNA level and suppressed HMGR gene expression. Meanwhile, upon berberine-treated rats, there was a significant increase in apolipoprotein E (apoE) mRNA, but no change in apoAI and scavenger receptor (SR) mRNA in the liver. Further, no atherosclerotic lesions were developed in berberine-treated rats for 16 weeks.

Conclusion

Berberine can counteract HFD-elicited hyperhomocysteinemia and hyperlipidemia partially via upregulating LDLR and apoE mRNA levels and suppressing HMGR gene expression.

Background

In plants, pollination is a critical step in reproduction. During pollination, constant communication between male pollen and the female stigma is required for pollen adhesion, germination, and tube growth. The detailed mechanisms of stigma-mediated reproductive processes, however, remain largely unknown. Maize (Zea mays L.), one of the world’s most important crops, has been extensively used as a model species to study molecular mechanisms of pollen and stigma interaction. A comprehensive analysis of maize silk transcriptome may provide valuable information for investigating stigma functionality. A comparative analysis of expression profiles between maize silk and dry stigmas of other species might reveal conserved and diverse mechanisms that underlie stigma-mediated reproductive processes in various plant species.

Results

Transcript abundance profiles of mature silk, mature pollen, mature ovary, and seedling were investigated using RNA-seq. By comparing the transcriptomes of these tissues, we identified 1,427 genes specifically or preferentially expressed in maize silk. Bioinformatic analyses of these genes revealed many genes with known functions in plant reproduction as well as novel candidate genes that encode amino acid transporters, peptide and oligopeptide transporters, and cysteine-rich receptor-like kinases. In addition, comparison of gene sets specifically or preferentially expressed in stigmas of maize, rice (Oryza sativa L.), and Arabidopsis (Arabidopsis thaliana [L.] Heynh.) identified a number of homologous genes involved either in pollen adhesion, hydration, and germination or in initial growth and penetration of pollen tubes into the stigma surface. The comparison also indicated that maize shares a more similar profile and larger number of conserved genes with rice than with Arabidopsis, and that amino acid and lipid transport-related genes are distinctively overrepresented in maize.

Conclusions

Many of the novel genes uncovered in this study are potentially involved in stigma-mediated reproductive processes, including genes encoding amino acid transporters, peptide and oligopeptide transporters, and cysteine-rich receptor-like kinases. The data also suggest that dry stigmas share similar mechanisms at early stages of pollen-stigma interaction. Compared with Arabidopsis, maize and rice appear to have more conserved functional mechanisms. Genes involved in amino acid and lipid transport may be responsible for mechanisms in the reproductive process that are unique to maize silk.

With rapid advances in the development of DNA sequencing technologies, a plethora of high-throughput genome and proteome data from a diverse spectrum of organisms have been generated. The functional annotation and evolutionary history of proteins are usually inferred from domains predicted from the genome sequences. Traditional database-based domain prediction methods cannot identify novel domains, however, and alignment-based methods, which look for recurring segments in the proteome, are computationally demanding. Here, we propose a novel genome-wide domain prediction method, SECOM. Instead of conducting all-against-all sequence alignment, SECOM first indexes all the proteins in the genome by using a hash seed function. Local similarity can thus be detected and encoded into a graph structure, in which each node represents a protein sequence and each edge weight represents the shared hash seeds between the two nodes. SECOM then formulates the domain prediction problem as an overlapping community-finding problem in this graph. A backward graph percolation algorithm that efficiently identifies the domains is proposed. We tested SECOM on five recently sequenced genomes of aquatic animals. Our tests demonstrated that SECOM was able to identify most of the known domains identified by InterProScan. When compared with the alignment-based method, SECOM showed higher sensitivity in detecting putative novel domains, while it was also three orders of magnitude faster. For example, SECOM was able to predict a novel sponge-specific domain in nucleoside-triphosphatase (NTPases). Furthermore, SECOM discovered two novel domains, likely of bacterial origin, that are taxonomically restricted to sea anemone and hydra. SECOM is an open-source program and available at http://sfb.kaust.edu.sa/Pages/Software.aspx.

Objective. We aim to study the therapeutic effects of scraping by investigating the changes of temperature and local blood perfusion volume in healthy subjects after scraping stimulation, and to explore the mechanism of scraping stimulation from the points of microcirculation and energy metabolism. Methods. Twenty-three health subjects were included in this study. Local blood perfusion volume and body surface temperature was detected at 5 min before scraping stimulation, 0, 15, 30, 60 and 90 min after scraping using Laser Doppler imager and infrared thermograph. Results. Significant increase was noted in the blood perfusion volume in the scraping area within 90 minutes compared to the baseline level and non-scraping area (P < 0.001). Compared with non-scraping area, an increase of body temperature with an average of 1°C was observed after scraping stimulation (P < 0.01). Conclusion. Scraping can significantly improve the blood perfusion volume and increase the temperature in the scraping area, promoting the local blood circulation and energy metabolism.