bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive functional differentiation of dendritic cells: integrating the network of extra- and intracellular signals
Authors: Luft Thomas , Rodionova Elena , Maraskovsky Eugene , Kirsch Michael , Hess Michael , Buchholtz Christian , Goerner Martin , Schnurr Max , Skoda Radek , Ho Anthony D. 
Published: March 2006

AbstractPhenotypic maturation, cytokine secretion, and migration are distinct functional characteristics of dendritic cells (DCs). These functions are independently regulated by a number of extracellular variables, such as type, strength, and persistence of an array of soluble and membrane-bound mediators. Since the exact composition of these variables in response to infection may differ between individuals, the intracellular signaling pathways activated by these extracellular networks may more closely correlate with DC function and predict the course of adaptive immunity. We found that activation of p38 kinase (p38K), extracellular signal–related kinase 1/2 (ERK1/2), and phosphatidylcholine-specific phospholipase C (PC-PLC) enhanced cytokine secretion, whereas p38K, cyclic adenosine monophosphate (cAMP), and PC-PLC enhanced migration. In contrast, phosphatidylinositol 3-kinase (PI3K)/Akt-1 and cAMP inhibited cytokine secretion while ERK1/2 inhibited migration. Migration and cytokine secretion further differed in their sensitivity to inhibition over time. However, although DCs could be manipulated to express migration, cytokine secretion, or both, the level of activation or persistence of intracellular pathway signaling was not predictive. Our results suggest a modular organization of function. We hypothesize that the expression of specific DC functions integrates a large variety of activating and inhibitory variables, and is represented by the formation of a functional unit of molecular networks—the signal response module (SRM). The combined activities of these modules define the functional outcome of DC activation.
Superior effects of high-dose enzyme replacement therapy in type 1 Gaucher disease on bone marrow involvement and chitotriosidase levels: a 2-center retrospective analysis
Authors: de Fost Maaike , Hollak Carla E. M. , Groener Johanna E. M. , Aerts Johannes M. F. G. , Maas Mario , Poll Ludger W. , Wiersma Maaike G. , Häussinger Dieter , Brett Sarah , Brill Nicole , Dahl Stephan vom 
Published: March 2006

AbstractDosing of enzyme replacement therapy (ERT) for Gaucher disease type 1 is still a subject of debate and varies from 15 to 130 U/kg/mo, making a huge economic difference of US $70 000 to US $380 000 (€55 000-300 000) per patient per year. To investigate whether this difference in dosing ultimately translates into a different response, we retrospectively compared long-term outcome of ERT at 2 large European treatment centers, Academic Medical Center, Amsterdam, The Netherlands (n = 49, median dose, 15-30 U/kg/4 wks) and Heinrich-Heine University, Duesseldorf, Germany (n = 57, median dose, 80 U/kg/4 wks). These adult cohorts had a similar genetic background. All follow-up parameters were matched separately at baseline, to avoid bias with respect to disease severity. Improvement in hemoglobin, platelet count, and hepatosplenomegaly was not significantly different between both cohorts, whereas plasma chitotriosidase and bone marrow involvement by magnetic resonance imaging improved more quickly and was more pronounced in the higher-dosed group. Major bone complications rarely occurred in both groups. In conclusion, different dosing regimens of ERT do not affect outcome of hematologic and visceral parameters, but higher dosing leads to accelerated decrease of chitotriosidase and better objective bone response in adult type 1 Gaucher disease.
VEGF is upregulated by hypoxia-induced mitogenic factor via the PI-3K/Akt-NF-κB signaling pathway
Authors: Tong Qiangsong , Zheng Liduan , Lin Li , Li Bo , Wang Danming , Huang Chuanshu , Li Dechun 
Published: March 2006

Abstract

Background
Hypoxia-induced mitogenic factor (HIMF) is developmentally regulated and plays an important role in lung pathogenesis. We initially found that HIMF promotes vascular tubule formation in a matrigel plug model. In this study, we investigated the mechanisms which HIMF enhances expression of vascular endothelial growth factor (VEGF) in lung tissues and epithelial cells.

Methods
Recombinant HIMF protein was intratracheally instilled into adult mouse lungs, VEGF expression was examined by immunohistochemical staining and Western blot. The promoter-luciferase reporter assay, RT-PCR, and Western blot were performed to examine the effects of HIMF on VEGF expression in mouse lung epithelial cell line MLE-12. The activation of NF-kappa B (NF-κB) and phosphorylation of Akt, IKK and IκBα were examined by luciferase assay and Western blot, respectively.

Results
Intratracheal instillation of HIMF protein resulted in significant increase of VEGF, mainly localized to airway epithelial and alveolar type II cells. Deletion of NF-κB binding sites within VEGF promoter abolished HIMF-induced VEGF expression in MLE-12 cells, suggesting that activation of NF-κB is essential for VEGF upregulation induced by HIMF. Stimulation of lung epithelial cells by HIMF resulted in phosphorylation of IKK and IκBα, leading to activation of NF-κB. In addition, HIMF strongly induced Akt phosphorylation, and suppression of Akt activation by specific inhibitors and dominant negative mutants for PI-3K, and IKK or IκBα blocked HIMF-induced NF-κB activation and attenuated HIMF-induced VEGF production.

Conclusion
These results suggest that HIMF enhances VEGF production in mouse lung epithelial cells in a PI-3K/Akt-NF-κB signaling pathway-dependent manner, and may play critical roles in pulmonary angiogenesis.
Farnesylation or geranylgeranylation? Efficient assays for testing protein prenylation in vitro and in vivo
Authors: Benetka Wolfgang , Koranda Manfred , Maurer-Stroh Sebastian , Pittner Fritz , Eisenhaber Frank 
Published: March 2006

Abstract

Background
Available in vitro and in vivo methods for verifying protein substrates for posttranslational modifications via farnesylation or geranylgeranylation (for example, autoradiography with 3H-labeled anchor precursors) are time consuming (weeks/months), laborious and suffer from low sensitivity.

Results
We describe a new technique for detecting prenyl anchors in N-terminally glutathione S-transferase (GST)-labeled constructs of target proteins expressed in vitro in rabbit reticulocyte lysate and incubated with 3H-labeled anchor precursors. Alternatively, hemagglutinin (HA)-labeled constructs expressed in vivo (in cell culture) can be used. For registration of the radioactive marker, we propose to use a thin layer chromatography (TLC) analyzer. As a control, the protein yield is tested by Western blotting with anti-GST- (or anti-HA-) antibodies on the same membrane that has been previously used for TLC-scanning. These protocols have been tested with Rap2A, v-Ki-Ras2 and RhoA (variant RhoA63L) including the necessary controls. We show directly that RasD2 is a farnesylation target.

Conclusion
Savings in time for experimentation and the higher sensitivity for detecting 3H-labeled lipid anchors recommend the TLC-scanning method with purified GST- (or HA-) tagged target proteins as the method of choice for analyzing their prenylation capabilities in vitro and in vivo and, possibly, also for studying the myristoyl and palmitoyl posttranslational modifications.
The protein kinase DYRK1A phosphorylates the splicing factor SF3b1/SAP155 at Thr434, a novel in vivo phosphorylation site
Authors: de Graaf Katrin , Czajkowska Hanna , Rottmann Sabine , Packman Len C , Lilischkis Richard , Lüscher Bernhard , Becker Walter 
Published: March 2006

Abstract

Background
The U2 small nuclear ribonucleoprotein particle (snRNP) component SF3b1/SAP155 is the only spliceosomal protein known to be phosphorylated concomitant with splicing catalysis. DYRK1A is a nuclear protein kinase that has been localized to the splicing factor compartment. Here we describe the identification of DYRK1A as a protein kinase that phosphorylates SF3b1 in vitro and in cultivated cells.

Results
Overexpression of DYRK1A caused a markedly increased phosphorylation of SF3b1 in COS-7 cells as assessed by Western blotting with an antibody specific for phosphorylated Thr-Pro dipeptide motifs. Phosphopeptide mapping of metabolically labelled SF3b1 showed that the majority of the in vivo-phosphopeptides corresponded to sites also phosphorylated by DYRK1A in vitro. Phosphorylation with cyclin E/CDK2, a kinase previously reported to phosphorylate SF3b1, generated a completely different pattern of phosphopeptides. By mass spectrometry and mutational analysis of SF3b1, Thr434 was identified as the major phosphorylation site for DYRK1A. Overexpression of DYRK1A or the related kinase, DYRK1B, resulted in an enhanced phosphorylation of Thr434 in endogenous SF3b1 in COS-7 cells. Downregulation of DYRK1A in HEK293 cells or in HepG2 cells by RNA interference reduced the phosphorylation of Thr434 in SF3b1.

Conclusion
The present data show that the splicing factor SF3b1 is a substrate of the protein kinase DYRK1A and suggest that DYRK1A may be involved in the regulation of pre mRNA-splicing.
Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method
Authors: Bengtsson Henrik , Hössjer Ola 
Published: March 2006

Abstract

Background
Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple methods have been suggested to date, but it is not clear which is the best. It is therefore important to further study the different normalization methods in detail and the nature of microarray data in general.

Results
A methodological study of affine models for gene expression data is carried out. Focus is on two-channel comparative studies, but the findings generalize also to single- and multi-channel data. The discussion applies to spotted as well as in-situ synthesized microarray data. Existing normalization methods such as curve-fit ("lowess") normalization, parallel and perpendicular translation normalization, and quantile normalization, but also dye-swap normalization are revisited in the light of the affine model and their strengths and weaknesses are investigated in this context. As a direct result from this study, we propose a robust non-parametric multi-dimensional affine normalization method, which can be applied to any number of microarrays with any number of channels either individually or all at once. A high-quality cDNA microarray data set with spike-in controls is used to demonstrate the power of the affine model and the proposed normalization method.

Conclusion
We find that an affine model can explain non-linear intensity-dependent systematic effects in observed log-ratios. Affine normalization removes such artifacts for non-differentially expressed genes and assures that symmetry between negative and positive log-ratios is obtained, which is fundamental when identifying differentially expressed genes. In addition, affine normalization makes the empirical distributions in different channels more equal, which is the purpose of quantile normalization, and may also explain why dye-swap normalization works or fails. All methods are made available in the aroma package, which is a platform-independent package for R.
SinicView: A visualization environment for comparisons of multiple nucleotide sequence alignment tools
Authors: Shih Arthur Chun-Chieh , Lee DT , Lin Laurent , Peng Chin-Lin , Chen Shiang-Heng , Wu Yu-Wei , Wong Chun-Yi , Chou Meng-Yuan , Shiao Tze-Chang , Hsieh Mu-Fen 
Published: March 2006

Abstract

Background
Deluged by the rate and complexity of completed genomic sequences, the need to align longer sequences becomes more urgent, and many more tools have thus been developed. In the initial stage of genomic sequence analysis, a biologist is usually faced with the questions of how to choose the best tool to align sequences of interest and how to analyze and visualize the alignment results, and then with the question of whether poorly aligned regions produced by the tool are indeed not homologous or are just results due to inappropriate alignment tools or scoring systems used. Although several systematic evaluations of multiple sequence alignment (MSA) programs have been proposed, they may not provide a standard-bearer for most biologists because those poorly aligned regions in these evaluations are never discussed. Thus, a tool that allows cross comparison of the alignment results obtained by different tools simultaneously could help a biologist evaluate their correctness and accuracy.

Results
In this paper, we present a versatile alignment visualization system, called SinicView, (for Sequence-aligning INnovative and Interactive Comparison VIEWer), which allows the user to efficiently compare and evaluate assorted nucleotide alignment results obtained by different tools. SinicView calculates similarity of the alignment outputs under a fixed window using the sum-of-pairs method and provides scoring profiles of each set of aligned sequences. The user can visually compare alignment results either in graphic scoring profiles or in plain text format of the aligned nucleotides along with the annotations information. We illustrate the capabilities of our visualization system by comparing alignment results obtained by MLAGAN, MAVID, and MULTIZ, respectively.

Conclusion
With SinicView, users can use their own data sequences to compare various alignment tools or scoring systems and select the most suitable one to perform alignment in the initial stage of sequence analysis.
SCOWLP: a web-based database for detailed characterization and visualization of protein interfaces
Authors: Teyra Joan , Doms Andreas , Schroeder Michael , Pisabarro M Teresa 
Published: March 2006

Abstract

Background
Currently there is a strong need for methods that help to obtain an accurate description of protein interfaces in order to be able to understand the principles that govern molecular recognition and protein function. Many of the recent efforts to computationally identify and characterize protein networks extract protein interaction information at atomic resolution from the PDB. However, they pay none or little attention to small protein ligands and solvent. They are key components and mediators of protein interactions and fundamental for a complete description of protein interfaces. Interactome profiling requires the development of computational tools to extract and analyze protein-protein, protein-ligand and detailed solvent interaction information from the PDB in an automatic and comparative fashion. Adding this information to the existing one on protein-protein interactions will allow us to better understand protein interaction networks and protein function.

Description
SCOWLP (S tructural C haracterization O f W ater, L igands and P roteins) is a user-friendly and publicly accessible web-based relational database for detailed characterization and visualization of the PDB protein interfaces. The SCOWLP database includes proteins, peptidic-ligands and interface water molecules as descriptors of protein interfaces. It contains currently 74,907 protein interfaces and 2,093,976 residue-residue interactions formed by 60,664 structural units (protein domains and peptidic-ligands) and their interacting solvent.
The SCOWLP web-server allows detailed structural analysis and comparisons of protein interfaces at atomic level by text query of PDB codes and/or by navigating a SCOP-based tree. It includes a visualization tool to interactively display the interfaces and label interacting residues and interface solvent by atomic physicochemical properties. SCOWLP is automatically updated with every SCOP release.

Conclusion
SCOWLP enriches substantially the description of protein interfaces by adding detailed interface information of peptidic-ligands and solvent to the existing protein-protein interaction databases. SCOWLP may be of interest to many structural bioinformaticians. It provides a platform for automatic global mapping of protein interfaces at atomic level, representing a useful tool for classification of protein interfaces, protein binding comparative studies, reconstruction of protein complexes and understanding protein networks. The web-server with the database and its additional summary tables used for our analysis are available at http://www.scowlp.org.
A quantitative analysis of secondary RNA structure using domination based parameters on trees
Authors: Haynes Teresa , Knisley Debra , Seier Edith , Zou Yue 
Published: March 2006

Abstract

Background
It has become increasingly apparent that a comprehensive database of RNA motifs is essential in order to achieve new goals in genomic and proteomic research. Secondary RNA structures have frequently been represented by various modeling methods as graph-theoretic trees. Using graph theory as a modeling tool allows the vast resources of graphical invariants to be utilized to numerically identify secondary RNA motifs. The domination number of a graph is a graphical invariant that is sensitive to even a slight change in the structure of a tree. The invariants selected in this study are variations of the domination number of a graph. These graphical invariants are partitioned into two classes, and we define two parameters based on each of these classes. These parameters are calculated for all small order trees and a statistical analysis of the resulting data is conducted to determine if the values of these parameters can be utilized to identify which trees of orders seven and eight are RNA-like in structure.

Results
The statistical analysis shows that the domination based parameters correctly distinguish between the trees that represent native structures and those that are not likely candidates to represent RNA. Some of the trees previously identified as candidate structures are found to be "very" RNA like, while others are not, thereby refining the space of structures likely to be found as representing secondary RNA structure.

Conclusion
Search algorithms are available that mine nucleotide sequence databases. However, the number of motifs identified can be quite large, making a further search for similar motif computationally difficult. Much of the work in the bioinformatics arena is toward the development of better algorithms to address the computational problem. This work, on the other hand, uses mathematical descriptors to more clearly characterize the RNA motifs and thereby reduce the corresponding search space. These preliminary findings demonstrate that graph-theoretic quantifiers utilized in fields such as computer network design hold significant promise as an added tool for genomics and proteomics.
IsoSVM – Distinguishing isoforms and paralogs on the protein level
Authors: Spitzer Michael , Lorkowski Stefan , Cullen Paul , Sczyrba Alexander , Fuellen Georg 
Published: March 2006

AbstractBackgroundRecent progress in cDNA and EST sequencing is yielding a deluge of sequence data. Like database search results and proteome databases, this data gives rise to inferred protein sequences without ready access to the underlying genomic data. Analysis of this information (e.g. for EST clustering or phylogenetic reconstruction from proteome data) is hampered because it is not known if two protein sequences are isoforms (splice variants) or not (i.e. paralogs/orthologs). However, even without knowing the intron/exon structure, visual analysis of the pattern of similarity across the alignment of the two protein sequences is usually helpful since paralogs and orthologs feature substitutions with respect to each other, as opposed to isoforms, which do not.ResultsThe IsoSVM tool introduces an automated approach to identifying isoforms on the protein level using a support vector machine (SVM) classifier. Based on three specific features used as input of the SVM classifier, it is possible to automatically identify isoforms with little effort and with an accuracy of more than 97%. We show that the SVM is superior to a radial basis function network and to a linear classifier. As an example application we use IsoSVM to estimate that a set ofXenopus laevisEST clusters consists of approximately 81% cases where sequences are each other's paralogs and 19% cases where sequences are each other's isoforms. The number of isoforms and paralogs in this allotetraploid species is of interest in the study of evolution.ConclusionWe developed an SVM classifier that can be used to distinguish isoforms from paralogs with high accuracy and without access to the genomic data. It can be used to analyze, for example, EST data and database search results. Our software is freely available on the Web, under the name IsoSVM.
Lower expression of genes near microRNA in C. elegans germline
Authors: Inaoka Hidenori , Fukuoka Yutaka , Kohane Isaac S 
Published: March 2006

Abstract

Background
MicroRNAs (miRNAs) are recently discovered short non-protein-coding RNA molecules. miRNAs are increasingly implicated in tissue-specific transcriptional control and particularly in development. Because there is mounting evidence for the localized component of transcriptional control, we investigated if there is a distance-dependent effect of miRNA.

Results
We analyzed gene expression levels around the 84 of 113 know miRNAs for which there are nearby gene that were measured in the data in two independent C. elegans expression data sets. The expression levels are lower for genes in the vicinity of 59 of 84 (71%) miRNAs as compared to genes far from such miRNAs. Analysis of the genes with lower expression in proximity to the miRNAs reveals increased frequency matching of the 7 nucleotide "seed"s of these miRNAs.

Conclusion
We found decreased messenger RNA (mRNA) abundance, localized within a 10 kb of chromosomal distance of some miRNAs, in C. elegans germline. The increased frequency of seed matching near miRNA can explain, in part, the localized effects.
MAGIC-SPP: a database-driven DNA sequence processing package with associated management tools
Authors: Liang Chun , Sun Feng , Wang Haiming , Qu Junfeng , Freeman Robert M , Pratt Lee H , Cordonnier-Pratt Marie-Michèle 
Published: March 2006

AbstractBackgroundProcessing raw DNA sequence data is an especially challenging task for relatively small laboratories and core facilities that produce as many as 5000 or more DNA sequences per week from multiple projects in widely differing species. To meet this challenge, we have developed the flexible, scalable, and automated sequence processing package described here.ResultsMAGIC-SPP is a DNA sequence processing package consisting of an Oracle 9i relational database, a Perl pipeline, and user interfaces implemented either as JavaServer Pages (JSP) or as a Java graphical user interface (GUI). The database not only serves as a data repository, but also controls processing of trace files. MAGIC-SPP includes an administrative interface, a laboratory information management system, and interfaces for exploring sequences, monitoring quality control, and troubleshooting problems related to sequencing activities. In the sequence trimming algorithm it employs new features designed to improve performance with respect to concerns such as concatenated linkers, identification of the expected start position of a vector insert, and extending the useful length of trimmed sequences by bridging short regions of low quality when the following high quality segment is sufficiently long to justify doing so.ConclusionMAGIC-SPP has been designed to minimize human error, while simultaneously being robust, versatile, flexible and automated. It offers a unique combination of features that permit administration by a biologist with little or no informatics background. It is well suited to both individual research programs and core facilities.