bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of hydraulic nozzle flow rate and high injection pressure on mixture formation, combustion and emissions on a single-cylinder DI light-duty diesel engine
Authors: Rollbusch Carsten 
Published: December 2011

Injection pressure and hydraulic nozzle flow rate are significant parameters that influence mixture formation and combustion in the direct injection (DI) diesel combustion process. An injection pressure increase enhances mixture formation as well as combustion. Decreasing the hydraulic flow rate, by means of reducing spray hole orifice diameter, affects mixture formation primarily through improved gas entrainment processes. Both injection pressure increase and hydraulic flow rate decrease therefore benefit mixture formation and combustion, which cause less soot emissions. Thus, the application of higher exhaust gas recirculation rates to decrease nitrogen oxide emissions is possible. The objective of this paper is to determine the effects of hydraulic flow rate variation in combination with very high injection pressures. Engine tests are carried out using a single-cylinder research engine, which is based on a light-duty DI diesel engine. With a displacement of 755 cm3 per cylinder, the engines range between typical passenger car (≈ 500 cm3) and medium-sized heavy-duty (≈ 1000 cm3) engines. The engine is equipped with a prototype common rail fuel injection system that is capable of delivering system pressures larger than 250 MPa. Four different hydraulic nozzle layouts are tested. The effects are presented for one part load and one full load operating condition. For each engine operating point, exhaust gas recirculation variations with different injection pressure levels and boost conditions are conducted. Evaluation of engine test results is performed at a constant soot/nitrogen oxide emission ratio of 1:10, which is relevant in engine calibration. Hydraulic measurements and the application of an empirical spray model support the interpretation of the engine test results. It is observed that a reduced hydraulic flow rate is beneficial for part load emission performance. It was found that a lower hydraulic flow rate causes a higher mean relative air/fuel ratio within the fuel spray and thus induces less soot formation. Moreover, the premixed fraction of combustion is enhanced through both injection pressure and hydraulic flow rate increases. In full load operation, the beneficial effect of reduced flow rates by means of smaller nozzle orifices cannot be detected. Parameters such as injection duration, combustion duration and spray momentum during spray/wall interaction are identified as more important. Boost pressure variation has only a minor effect on part load, whereas full load results are greatly influenced. In part load and full load operation, a limitation of the potential to reduce emissions is not observed within the investigated injection pressure range.
Learning the structure of gene regulatory networks from time series gene expression data
Authors: Li Haoni , Wang Nan , Gong Ping , Perkins Edward J , Zhang Chaoyang 
Published: December 2011

Abstract

Background
Dynamic Bayesian Network (DBN) is an approach widely used for reconstruction of gene regulatory networks from time-series microarray data. Its performance in network reconstruction depends on a structure learning algorithm. REVEAL (REVerse Engineering ALgorithm) is one of the algorithms implemented for learning DBN structure and used to reconstruct gene regulatory networks (GRN). However, the two-stage temporal Bayes network (2TBN) structure of DBN that specifies correlation between time slices cannot be obtained by score metrics used in REVEAL.

Methods
In this paper, we study a more sophisticated score function for DBN first proposed by Nir Friedman for stationary DBNs structure learning of both initial and transition networks but has not yet been used for reconstruction of GRNs. We implemented Friedman's Bayesian Information Criterion (BIC) score function, modified K2 algorithm to learn Dynamic Bayesian Network structure with the score function and tested the performance of the algorithm for GRN reconstruction with synthetic time series gene expression data generated by GeneNetWeaver and real yeast benchmark experiment data.

Results
We implemented an algorithm for DBN structure learning with Friedman's score function, tested it on reconstruction of both synthetic networks and real yeast networks and compared it with REVEAL in the absence or presence of preprocessed network generated by Zou&Conzen's algorithm. By introducing a stationary correlation between two consecutive time slices, Friedman's score function showed a higher precision and recall than the naive REVEAL algorithm.

Conclusions
Friedman's score metrics for DBN can be used to reconstruct transition networks and has a great potential to improve the accuracy of gene regulatory network structure prediction with time series gene expression datasets.
Functional complementation between transcriptional methylation regulation and post-transcriptional microRNA regulation in the human genome
Authors: Su Zhixi , Xia Junfeng , Zhao Zhongming 
Published: December 2011

Abstract

Background
DNA methylation in the 5' promoter regions of genes and microRNA (miRNA) regulation at the 3' untranslated regions (UTRs) are two major epigenetic regulation mechanisms in most eukaryotes. Both DNA methylation and miRNA regulation can suppress gene expression and their corresponding protein product; thus, they play critical roles in cellular processes. Although there have been numerous investigations of gene regulation by methylation changes and miRNAs, there is no systematic genome-wide examination of their coordinated effects in any organism.

Results
In this study, we investigated the relationship between promoter methylation at the transcription level and miRNA regulation at the post-transcription level by taking advantage of recently released human methylome data and high quality miRNA and other gene annotation data. We found methylation level in the promoter regions and expression level was negatively correlated. Then, we showed that miRNAs tended to target the genes with a low DNA methylation level in their promoter regions. We further demonstrated that this observed pattern was not attributed to the gene expression level, expression broadness, or the number of transcription factor binding sites. Interestingly, we found miRNA target sites were significantly enriched in the genes located in differentially methylated regions or partially methylated domains. Finally, we explored the features of DNA methylation and miRNA regulation in cancer genes and found cancer genes tended to have low methylation level and more miRNA target sites.

Conclusion
This is the first genome-wide investigation of the combined regulation of gene expression. Our results supported a complementary regulation between DNA methylation (transcriptional level) and miRNA function (post-transcriptional level) in the human genome. The results were helpful for our understanding of the evolutionary forces towards organisms' complexity beyond traditional sequence level investigation.
Protease-associated cellular networks in malaria parasite Plasmodium falciparum
Authors: Lilburn Timothy G , Cai Hong , Zhou Zhan , Wang Yufeng 
Published: December 2011

AbstractBackgroundMalaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome) in the malaria parasitePlasmodium falciparumand its sibling species [1–3], providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases ofP. falciparum.ResultsWe investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database [4], and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H) system [5], blood stage microarray experiments [6–8], proteomics [9–12], literature text mining, and sequence homology analysis. Seventy-seven (77) out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs). These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins), range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide processing, cell cycle progression, transcriptional regulation, and signal transduction networks.ConclusionsOur network analysis of proteases fromP. falciparumuses a so-called guilt-by-association approach to extract sets of proteins from the proteome that are candidates for further study. Novel protease targets and previously unrecognized members of the protease-associated sub-systems provide new insights into the mechanisms underlying parasitism, pathogenesis and virulence.
Circulating LH/hCG receptor (LHCGR) may identify pre-treatment IVF patients at risk of OHSS and poor implantation
Authors: Chambers Anne E , Nayini Krishnaveni P , Mills Walter E , Lockwood Gillian M , Banerjee Subhasis 
Published: December 2011

Abstract

Background
Successful pregnancy via in vitro fertilization (IVF) depends on the recovery of an adequate number of healthy oocytes and on blastocyst implantation following uterine transfer. Two hormones, LH and hCG, utilize a common LH/hCG receptor (LHCGR), variations in which have profound implications in human reproduction. Soluble LHCGR (sLHCGR) is released from experimental cell lines and placental explants and it can be detected in the follicular fluid and serum.

Methods
To evaluate the impact of circulating soluble LHCGR (sLHCGR) in fertility treatment, we measured sLHCGR and LH-sLHCGR complex in serum from women seeking IVF using specifically developed quantitative enzyme-linked immunosorbent assays (ELISA). Following an IVF cycle of treatment, patients were grouped according to oocyte yield into low (lower than or equal to 7 oocytes), intermediate (8-14 oocytes) and high (greater than or equal to 15 oocytes) responders and pregnancy outcome noted.

Results
Pre-treatment sLHCGR identified many women at risk of ovarian hyperstimulation. Low levels of sLHCGR were associated with pregnancy in both high and low responders but sLHCGR did not significantly affect the treatment outcome of intermediate responders. Low responders who failed to become pregnant had high levels of circulating sLHCGR bound to LH (LH-sLHCGR).

Conclusions
Pre-treatment measurement of sLHCGR could be used to tailor individual fertility treatment programs and improve outcomes by avoiding ovarian hyperstimulation and poor embryo implantation.
Interferon regulatory factor-7 modulates experimental autoimmune encephalomyelitis in mice
Authors: Salem Mohammad , Mony Jyothi T , Løbner Morten , Khorooshi Reza , Owens Trevor 
Published: December 2011

AbstractBackgroundMultiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS) with unknown etiology. Interferon-β (IFN-β), a member of the type I IFN family, is used as a therapeutic for MS and the IFN signaling pathway is implicated in MS susceptibility. Interferon regulatory factor 7 (IRF7) is critical for the induction and positive feedback regulation of type I IFN. To establish whether and how endogenous type I IFN signaling contributes to disease modulation and to better understand the underlying mechanism, we examined the role of IRF7 in the development of MS-like disease in mice.MethodsThe role of IRF7 in development of EAE was studied by immunizing IRF7-KO and C57BL/6 (WT) mice with myelin oligodendrocyte glycoprotein using a standard protocol for the induction of EAE. We measured leukocyte infiltration and localization in the CNS using flow cytometric analysis and immunohistochemical procedures. We determined levels of CD3 and selected chemokine and cytokine gene expression by quantitative real-time PCR.ResultsIRF7 gene expression increased in the CNS as disease progressed. IRF7 message was localized to microglia and infiltrating leukocytes. Furthermore, IRF7-deficient mice developed more severe disease. Flow cytometric analysis showed that the extent of leukocyte infiltration into the CNS was higher in IRF7-deficient mice with significantly higher number of infiltrating macrophages and T cells, and the distribution of infiltrates within the spinal cord was altered. Analysis of cytokine and chemokine gene expression by quantitative real-time PCR showed significantly greater increases in CCL2, CXCL10, IL-1β and IL17 gene expression in IRF7-deficient mice compared with WT mice.ConclusionTogether, our findings suggest that IRF7 signaling is critical for regulation of inflammatory responses in the CNS.
Generation of recombinant Orfvirus using an enhanced green fluorescent protein reporter gene as a selectable marker
Authors: Ning Zhangyong , Peng Yongzheng , Hao Wenbo , Duan Chaohui , Rock Daniel L , Luo Shuhong 
Published: December 2011

Abstract

Background
Reporter genes are often used as a selectable marker for generation of recombinant viruses in order to investigate the mechanism of pathogenesis and to obtain candidate vaccine viruses. Routine selection of the recombinant parapoxvirus is time-consuming and labor intensive. Therefore, developing a novel method for selection is critical.

Results
In this study, we developed a rapid method to generate recombinant Orf viruses (ORFV) based on the enhanced green fluorescent protein (EGFP) reporter gene as a selectable marker. The coding sequence of EGFP gene was amplified from pEGFP-N1 vector and subcloned into the pZIPPY-neo/gus plasmid under the control of the early-late vaccinia virus (VACV) VV7.5 promoter and flanked by two multiple cloning sites (MCS) to generate a novel transfer vector pSPV-EGFP. Using the pSPV-EGFP, two recombination cassettes pSPV-113LF-EGFP-113RF and pSPV-116LF-EGFP-116RF were constructed by cloning the flanking regions of the ORFV113 and ORFV116 and inserted into two MCS flanking the EGFP gene. Using this novel system, two single gene deletion mutants OV-IA82Δ113 and OV-IA82Δ116 were successfully generated.

Conclusions
This approach shortens the time needed to generate recombinant ORFVs (rORFVs). Thus, the pSPV-EGFP vector provides a direct, fast, and convenient way to manipulate the recombinant viruses, indicating that it is highly suited for its designed purpose.
Ovarian vein thrombosis mimicking acute abdomen: a case report and literature review
Authors: Arkadopoulos Nikolaos , Dellaportas Dionysios , Yiallourou Anneza , Koureas Andreas , Voros Dionysios 
Published: December 2011

AbstractBackgroundOvarian vein thrombosis (OVT) is a rare, but serious condition that affects mostly postpartum women. A high index of suspicion is required in order to diagnose this unusual cause of abdominal pain.Case presentationA 19-year-old woman at three days postpartum was admitted to our hospital because of severe right lower quandrant abdominal pain and fever 38.5'C. Physical examination revealed an acutely ill patient and right lower quadrant tenderness with positive rebound and Giordano signs. The patient underwent appendectomy which proved to be negative for acute appendicitis. Postoperatively fever and pain persisted and abdominal CT-scan with intravenous contrast agent demonstrated a thrombosed right ovarian vein. The patient was initiated on low-molecular weight heparin (LMWH) and antibiotic treatment and a month later a new abdominal CT-scan showed a patent right ovarian vein.DiscussionPathophysiologically, OVT is explained by Virchow's triad, because pregnancy is associated with a hypercoagulable state, venous stasis due to compression of the inferior vena cava by the uterus and endothelial trauma during delivery or from local inflammation. Common symptoms and signs of OVT include lower abdomen or flank pain, fever and leukocytosis usually within the first ten days after delivery. The reported incidence of OVT ranges 0,05-0,18% of pregnancies and in most cases the right ovarian vein is the one affected. Anticoagulation and antibiotics is the mainstay of treatment of OVT. Complications of OVT include sepsis, extension of the thrombus to the inferior vena cava and renal veins, and pulmonary embolism. The incidence of pulmonary embolism is reported to be 13.2% and represents the main source of mortality due to OVT.ConclusionsOVT is a rare condition, usually in the postpartum period. A high index of suspicion is required for the prompt diagnosis and management especially in cases that mimic acute abdomen.
5'UTR mutations of ENG cause hereditary hemorrhagic telangiectasia
Authors: Damjanovich Kristy , Langa Carmen , Blanco Francisco J , McDonald Jamie , Botella Luisa M , Bernabeu Carmelo , Wooderchak-Donahue Whitney , Stevenson David A , Bayrak-Toydemir Pinar 
Published: December 2011

Abstract

Background
Hereditary hemorrhagic telangiectasia (HHT) is a vascular disorder characterized by epistaxis, arteriovenous malformations, and telangiectases. The majority of the patients have a mutation in the coding region of the activin A receptor type II-like 1 (ACVRL1) or Endoglin (ENG) gene. However, in approximately 15% of cases, sequencing analysis and deletion/duplication testing fail to identify mutations in the coding regions of these genes. Knowing its vital role in transcription and translation control, we were prompted to investigate the 5'untranslated region (UTR) of ENG.

Methods and Results
We sequenced the 5'UTR of ENG for 154 HHT patients without mutations in ENG or ACVRL1 coding regions. We found a mutation (c.-127C > T), which is predicted to affect translation initiation and alter the reading frame of endoglin. This mutation was found in a family with linkage to the ENG, as well as in three other patients, one of which had an affected sibling with the same mutation. In vitro expression studies showed that a construct with the c.-127C > T mutation alters the translation and decreases the level of the endoglin protein. In addition, a c.-9G > A mutation was found in three patients, one of whom was homozygous for this mutation. Expression studies showed decreased protein levels suggesting that the c.-9G > A is a hypomorphic mutation.

Conclusions
Our results emphasize the need for the inclusion of the 5'UTR region of ENG in clinical testing for HHT.
Leveraging social networks for understanding the evolution of epidemics
Authors: Martín Gonzalo , Marinescu Maria-Cristina , Singh David E , Carretero Jesús 
Published: December 2011

Abstract

Background
To understand how infectious agents disseminate throughout a population it is essential to capture the social model in a realistic manner. This paper presents a novel approach to modeling the propagation of the influenza virus throughout a realistic interconnection network based on actual individual interactions which we extract from online social networks. The advantage is that these networks can be extracted from existing sources which faithfully record interactions between people in their natural environment. We additionally allow modeling the characteristics of each individual as well as customizing his daily interaction patterns by making them time-dependent. Our purpose is to understand how the infection spreads depending on the structure of the contact network and the individuals who introduce the infection in the population. This would help public health authorities to respond more efficiently to epidemics.

Results
We implement a scalable, fully distributed simulator and validate the epidemic model by comparing the simulation results against the data in the 2004-2005 New York State Department of Health Report (NYSDOH), with similar temporal distribution results for the number of infected individuals. We analyze the impact of different types of connection models on the virus propagation. Lastly, we analyze and compare the effects of adopting several different vaccination policies, some of them based on individual characteristics -such as age- while others targeting the super-connectors in the social model.

Conclusions
This paper presents an approach to modeling the propagation of the influenza virus via a realistic social model based on actual individual interactions extracted from online social networks. We implemented a scalable, fully distributed simulator and we analyzed both the dissemination of the infection and the effect of different vaccination policies on the progress of the epidemics. The epidemic values predicted by our simulator match real data from NYSDOH. Our results show that our simulator can be a useful tool in understanding the differences in the evolution of an epidemic within populations with different characteristics and can provide guidance with regard to which, and how many, individuals should be vaccinated to slow down the virus propagation and reduce the number of infections.
An integrative analysis of DNA methylation and RNA-Seq data for human heart, kidney and liver
Authors: Xie Linglin , Weichel Brent , Ohm Joyce Ellen , Zhang Ke 
Published: December 2011

Abstract

Background
Many groups, including our own, have proposed the use of DNA methylation profiles as biomarkers for various disease states. While much research has been done identifying DNA methylation signatures in cancer vs. normal etc., we still lack sufficient knowledge of the role that differential methylation plays during normal cellular differentiation and tissue specification. We also need thorough, genome level studies to determine the meaning of methylation of individual CpG dinucleotides in terms of gene expression.

Results
In this study, we compiled unique DNA methylation signatures from normal human heart, lung, and kidney using the Illumina Infinium 27K methylation arrays and compared those to gene expression by RNA sequencing. We have identified unique signatures of global DNA methylation for human heart, kidney and liver, and showed that DNA methylation data can be used to correctly classify various tissues. It indicates that DNA methylation reflects tissue specificity and may play an important role in tissue differentiation. The integrative analysis of methylation and RNA-Seq data showed that gene methylation and its transcriptional levels were comprehensively correlated. The location of methylation markers in terms of distance to transcription start site and CpG island showed no effects on the regulation of gene expression by DNA methylation in normal tissues.

Conclusions
This study showed that an integrative analysis of methylation array and RNA-Seq data can be utilized to discover the global regulation of gene expression by DNA methylation and suggests that DNA methylation plays an important role in normal tissue differentiation via modulation of gene expression.