bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hyperglycemia enhances coagulation and reduces neutrophil degranulation, whereas hyperinsulinemia inhibits fibrinolysis during human endotoxemia
Authors: Stegenga Michiel E. , van der Crabben Saskia N. , Blümer Regje M. E. , Levi Marcel , Meijers Joost C. M. , Serlie Mireille J. , Tanck Michael W. T. , Sauerwein Hans P. , van der Poll Tom 
Published: March 2008

AbstractType 2 diabetes is associated with altered immune and hemostatic responses. We investigated the selective effects of hyperglycemia and hyperinsulinemia on innate immune, coagulation, and fibrinolytic responses during systemic inflammation. Twenty-four healthy humans were studied for 8 hours during clamp experiments in which either plasma glucose, insulin, both, or none was increased, depending on randomization. Target plasma concentrations were 5 versus 12 mM for glucose, and 100 versus 400 pmol/L for insulin. After 3 hours, 4 ng/kg Escherichia coli endotoxin was injected intravenously to induce a systemic inflammatory and procoagulant response. Endotoxin administration induced cytokine release, activation of neutrophils, endothelium and coagulation, and inhibition of fibrinolysis. Hyperglycemia reduced neutrophil degranulation (plasma elastase levels, P < .001) and exaggerated coagulation (plasma concentrations of thrombin-antithrombin complexes and soluble tissue factor, both P < .001). Hyperinsulinemia attenuated fibrinolytic activity due to elevated plasminogen activator-inhibitor-1 levels (P < .001). Endothelial cell activation markers and cytokine concentrations did not differ between clamps. We conclude that in humans with systemic inflammation induced by intravenous endotoxin administration hyperglycemia impairs neutrophil degranulation and potentiates coagulation, whereas hyperinsulinemia inhibits fibrinolysis. These data suggest that type 2 diabetes patients may be especially vulnerable to prothrombotic events during inflammatory states.
The human spleen is a major reservoir for long-lived vaccinia virus–specific memory B cells
Authors: Mamani-Matsuda Maria , Cosma Antonio , Weller Sandra , Faili Ahmad , Staib Caroline , Garçon Loïc , Hermine Olivier , Beyne-Rauzy Odile , Fieschi Claire , Pers Jacques-Olivier , Arakelyan Nina , Varet Bruno , Sauvanet Alain , Berger Anne , Paye François , Andrieu Jean-Marie , Michel Marc , Godeau Bertrand , Buffet Pierre , Reynaud Claude-Agnès , Weill Jean-Claude 
Published: March 2008

Abstract
The fact that you can vaccinate a child at 5 years of age and find lymphoid B cells and antibodies specific for this vaccination 70 years later remains an immunologic enigma. It has never been determined how these long-lived memory B cells are maintained and whether they are protected by storage in a special niche. We report that, whereas blood and spleen compartments present similar frequencies of IgG+ cells, antismallpox memory B cells are specifically enriched in the spleen where they account for 0.24% of all IgG+ cells (ie, 10-20 million cells) more than 30 years after vaccination. They represent, in contrast, only 0.07% of circulating IgG+ B cells in blood (ie, 50-100 000 cells). An analysis of patients either splenectomized or rituximab-treated confirmed that the spleen is a major reservoir for long-lived memory B cells. No significant correlation was observed between the abundance of these cells in blood and serum titers of antivaccinia virus antibodies in this study, including in the contrasted cases of B cell– depleting treatments. Altogether, these data provide evidence that in humans, the two arms of B-cell memory—long-lived memory B cells and plasma cells—have specific anatomic distributions—spleen and bone marrow—and homeostatic regulation.
A dual activation and inhibition role for the paired immunoglobulin-like receptor B in eosinophils
Authors: Munitz Ariel , McBride Melissa L. , Bernstein Joshua S. , Rothenberg Marc E. 
Published: March 2008

AbstractThe accumulation of eosinophils in inflammatory foci is a hallmark characteristic of Th2 inflammation. Nevertheless, the expression of inhibitory receptors such as paired immunoglobulin-like receptor B (PIR-B) and their function regulating eosinophil accumulation have received limited attention. We now report that Pirb was up-regulated in an eosinophil-dependent manner in the lungs of allergen-challenged and interleukin (IL)-13–overexpressing mice. Eosinophils expressed high levels of PIR-B, and Pirb−/− mice displayed increased gastrointestinal eosinophils. Consistent with these findings, PIR-B negatively regulated eotaxin-dependent eosinophil chemotaxis in vivo and in vitro. Surprisingly, Pirb−/− eosinophils and neutrophils had decreased leukotriene B4 (LTB4)–dependent chemotactic responses in vitro. Furthermore, eosinophil accumulation was decreased in a chitin-induced model, partially dependent on LTB4. Mechanistic analysis using a miniphosphoproteomic approach revealed that PIR-B recruits activating kinases after LTB4 but not eotaxin stimulation. Consequently, eotaxin-activated Pirb−/− eosinophils displayed markedly increased extracellular signal-related kinase 1 and 2 (ERK1/2) phosphorylation, whereas LTB4-activated eosinophils had reduced ERK1/2 phosphorylation. We provide multiple lines of evidence supporting a model in which PIR-B displays opposing but potent regulatory functions in granulocyte activation. These data change the conventional wisdom that inhibitory receptors are restricted to inhibitory signals; we therefore propose that a single receptor can have dual functionality in distinct cell types after unique cellular signals.
ProLoc-GO: Utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization
Authors: Huang Wen-Lin , Tung Chun-Wei , Ho Shih-Wen , Hwang Shiow-Fen , Ho Shinn-Ying 
Published: March 2008

AbstractBackgroundGene Ontology (GO) annotation, which describes the function of genes and gene products across species, has recently been used to predict protein subcellular and subnuclear localization. Existing GO-based prediction methods for protein subcellular localization use the known accession numbers of query proteins to obtain their annotated GO terms. An accurate prediction method for predicting subcellular localization of novel proteins without known accession numbers, using only the input sequence, is worth developing.ResultsThis study proposes an efficient sequence-based method (named ProLoc-GO) by mining informative GO terms for predicting protein subcellular localization. For each protein, BLAST is used to obtain a homology with a known accession number to the protein for retrieving the GO annotation. A large numbernof all annotated GO terms that have ever appeared are then obtained from a large set of training proteins. A novel genetic algorithm based method (named GOmining) combined with a classifier of support vector machine (SVM) is proposed to simultaneously identify a small numbermout of thenGO terms as input features to SVM, wherem<<n. Theminformative GO terms contain the essential GO terms annotating subcellular compartments such as GO:0005634 (Nucleus), GO:0005737 (Cytoplasm) and GO:0005856 (Cytoskeleton). Two existing data sets SCL12 (human protein with 12 locations) and SCL16 (Eukaryotic proteins with 16 locations) with <25% sequence identity are used to evaluate ProLoc-GO which has been implemented by using a single SVM classifier with them= 44 andm= 60 informative GO terms, respectively. ProLoc-GO using input sequences yields test accuracies of 88.1% and 83.3% for SCL12 and SCL16, respectively, which are significantly better than the SVM-based methods, which achieve < 35% test accuracies using amino acid composition (AAC) with acid pairs and AAC with dipedtide composition. For comparison, ProLoc-GO using known accession numbers of query proteins yields test accuracies of 90.6% and 85.7%, which is also better than Hum-PLoc (85.0%) and Euk-OET-PLoc (83.7%) using ensemble classifiers with hybridization of GO terms and amphiphilic pseudo amino acid composition for SCL12 and SCL16, respectively.ConclusionThe growth of Gene Ontology in size and popularity has increased the effectiveness of GO-based features. GOmining can serve as a tool for selecting informative GO terms in solving sequence-based prediction problems. The prediction system using ProLoc-GO with input sequences of query proteins for protein subcellular localization has been implemented (see Availability).
Comprehensive transcriptional profiling of prion infection in mouse models reveals networks of responsive genes
Authors: Sorensen Garrett , Medina Sarah , Parchaliuk Debra , Phillipson Clark , Robertson Catherine , Booth Stephanie A 
Published: March 2008

Abstract

Background
Prion infection results in progressive neurodegeneration of the central nervous system invariably resulting in death. The pathological effects of prion diseases in the brain are morphologically well defined, such as gliosis, vacuolation, and the accumulation of disease-specific protease-resistant prion protein (PrPSc). However, the underlying molecular events that lead to the death of neurons are poorly characterised.

Results
In this study cDNA microarrays were used to profile gene expression changes in the brains of two different strains of mice infected with three strains of mouse-adapted scrapie. Extensive data was collected and analyzed, from which we identified a core group of 349 prion-related genes (PRGs) that consistently showed altered expression in mouse models. Gene ontology analysis assigned many of the up-regulated genes to functional groups associated with one of the primary neuropathological features of prion diseases, astrocytosis and gliosis; protein synthesis, inflammation, cell proliferation and lipid metabolism. Using a computational tool, Ingenuity Pathway Analysis (IPA), we were able to build networks of interacting genes from the PRG list. The regulatory cytokine TGFB1, involved in modulating the inflammatory response, was identified as the outstanding interaction partner for many of the PRGs. The majority of genes expressed in neurons were down-regulated; a number of these were involved in regulatory pathways including synapse function, calcium signalling, long-term potentiation and ERK/MAPK signalling. Two down-regulated genes coding for the transcription regulators, EGR1 and CREB1, were also identified as central to interacting networks of genes; these factors are often used as markers of neuronal activity and their deregulation could be key to loss of neuronal function.

Conclusion
These data provides a comprehensive list of genes that are consistently differentially expressed in multiple scrapie infected mouse models. Building networks of interactions between these genes provides a means to understand the complex interplay in the brain during neurodegeneration. Resolving the key regulatory and signaling events that underlie prion pathogenesis will provide targets for the design of novel therapies and the elucidation of biomarkers.
Arsenic-induced changes in the gene expression of lung epithelial L2 cells: implications in carcinogenesis
Authors: Posey Tisha , Weng Tingting , Chen Zhongming , Chintagari Narendranath R , Wang Pengcheng , Jin Nili , Stricker Heidi , Liu Lin 
Published: March 2008

Abstract

Background
Arsenic is a carcinogen that is known to induce cell transformation and tumor formation. Although studies have been performed to examine the modulation of signaling molecules caused by arsenic exposure, the molecular mechanisms by which arsenic causes cancer are still unclear. We hypothesized that arsenic alters gene expression leading to carcinogenesis in the lung.

Results
In this study, we examined global gene expression in response to 0.75 μM arsenic treatment for 1–7 days in a rat lung epithelial cell line (L2) using an in-house 10 k rat DNA microarray. One hundred thirty one genes were identified using the one-class statistical analysis of microarray (SAM) test. Of them, 33 genes had a fold change of ≥ 2 between at least two time points. These genes were then clustered into 5 groups using K-means cluster analysis based on their expression patterns. Seven selected genes, all associated with cancer, were confirmed by real-time PCR. These genes have functions directly or indirectly related to metabolism, glycolysis, cell proliferation and differentiation, and regulation of transcription.

Conclusion
Our findings provide important insight for the future studies of arsenic-mediated lung cancer.
Antidepressant drugs modulate growth factors in cultured cells
Authors: Henkel Andreas W , Sperling Wolfgang , Rotter Andrea , Reulbach Udo , Reichardt Cornelia , Bönsch Dominikus , Maler Juan M , Kornhuber Johannes , Wiltfang Jens 
Published: March 2008

Abstract

Background
Different classes of antidepressant drugs are used as a treatment for depression by activating the catecholinergic system. In addition, depression has been associated with decrease of growth factors, which causes insufficient axonal sprouting and reduced neuronal damage repair. In this study, antidepressant treatments are analyzed in a cell culture system, to study the modulation of growth factors.

Results
We quantified the transcription of several growth factors in three cell lines after application of antidepressant drugs by real time polymerase chain reaction. Antidepressant drugs counteracted against phorbolester-induced deregulation of growth factors in PMA-differentiated neuronal SY5Y cells. We also found indications in a pilot experiment that magnetic stimulation could possibly modify BDNF in the cell culture system.

Conclusion
The antidepressant effects antidepressant drugs might be explained by selective modulation of growth factors, which subsequently affects neuronal plasticity.
Rice Yellow Mottle Virus stress responsive genes from susceptible and tolerant rice genotypes
Authors: Ventelon-Debout Marjolaine , Tranchant-Dubreuil Christine , Nguyen Thi-Thu-Huang , Bangratz Martine , Siré Christelle , Delseny Michel , Brugidou Christophe 
Published: March 2008

Abstract

Background
The effects of viral infection involve concomitant plant gene variations and cellular changes. A simple system is required to assess the complexity of host responses to viral infection. The genome of the Rice yellow mottle virus (RYMV) is a single-stranded RNA with a simple organisation. It is the most well-known monocotyledon virus model. Several studies on its biology, structure and phylogeography have provided a suitable background for further genetic studies. 12 rice chromosome sequences are now available and provide strong support for genomic studies, particularly physical mapping and gene identification.

Results
The present data, obtained through the cDNA-AFLP technique, demonstrate differential responses to RYMV of two different rice cultivars, i.e. susceptible IR64 (Oryza sativa indica), and partially resistant Azucena (O. s. japonica). This RNA profiling provides a new original dataset that will enable us to gain greater insight into the RYMV/rice interaction and the specificity of the host response. Using the SIM4 subroutine, we took the intron/exon structure of the gene into account and mapped 281 RYMV stress responsive (RSR) transcripts on 12 rice chromosomes corresponding to 234 RSR genes. We also mapped previously identified deregulated proteins and genes involved in partial resistance and thus constructed the first global physical map of the RYMV/rice interaction. RSR transcripts on rice chromosomes 4 and 10 were found to be not randomly distributed. Seven genes were identified in the susceptible and partially resistant cultivars, and transcripts were colocalized for these seven genes in both cultivars. During virus infection, many concomitant plant gene expression changes may be associated with host changes caused by the infection process, general stress or defence responses. We noted that some genes (e.g. ABC transporters) were regulated throughout the kinetics of infection and differentiated susceptible and partially resistant hosts.

Conclusion
We enhanced the first RYMV/rice interaction map by combining information from the present study and previous studies on proteins and ESTs regulated during RYMV infection, thus providing a more comprehensive view on genes related to plant responses. This combined map provides a new tool for exploring molecular mechanisms underlying the RYMV/rice interaction.
ERCC22251A>C genetic polymorphism was highly correlated with early relapse in high-risk stage II and stage III colorectal cancer patients: A preliminary study
Authors: Huang Ming-Yii , Fang Wei-Yu , Lee Su-Chen , Cheng Tian-Lu , Wang Jaw-Yuan , Lin Shiu-Ru 
Published: March 2008

Abstract

Background
Early relapse in colorectal cancer (CRC) patients is attributed mainly to the higher malignant entity (such as an unfavorable genotype, deeper tumor invasion, lymph node metastasis and advance cancer stage) and poor response to chemotherapy. Several investigations have demonstrated that genetic polymorphisms in drug-targeted genes, metabolizing enzymes, and DNA-repairing enzymes are all strongly correlated with inter-individual differences in the efficacy and toxicity of many treatment regimens. This preliminary study attempts to identify the correlation between genetic polymorphisms and clinicopathological features of CRC, and evaluates the relationship between genetic polymorphisms and chemotherapeutic susceptibility of Taiwanese CRC patients. To our knowledge, this study discusses, for the first time, early cancer relapse and its indication by multiple genes.

Methods
Six gene polymorphisms functional in drug-metabolism – GSTP1 Ile105Val, ABCB1 Ile1145Ile, MTHFR Ala222Val, TYMS double (2R) or triple (3R) tandem repeat – and DNA-repair genes – ERCC2 Lys751Gln and XRCC1 Arg399Gln – were assessed in 201 CRC patients using a polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP) technique and DNA sequencing. Patients were diagnosed as either high-risk stage II (T2 and 3 N0 M0) or III (any T N1 and 2 M0) and were administered adjuvant chemotherapy regimens that included 5-fluorouracil (5FU) and leucovorin (LV). The correlations between genetic polymorphisms and patient clinicopathological features and relapses were investigated.

Results
In this study, the distributions of GSTP1 (P = 0.003), ABCB1 (P = 0.001), TYMS (P < 0.0001), ERCC2 (P < 0.0001) and XRCC1 (P = 0.006) genotypes in the Asian population, with the exception of MTHFR (P = 0.081), differed significantly from their distributions in a Caucasian population. However, the unfavorable genotype ERCC2 2251A>C (P = 0.006), tumor invasion depth (P = 0.025), lymph node metastasis (P = 0.011) and cancer stage (P = 0.008) were significantly correlated with early relapse. Patients carrying the ERCC2 2251AC or2251CC genotypes had a significantly increased risk of early relapse (OR = 3.294, 95% CI, 1.272–8.532).

Conclusion
We suggest that ERCC2 2251A>C alleles may be genetic predictors of early CRC relapse.
New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients
Authors: Kohrt Holbrook E , Olshen Richard A , Bermas Honnie R , Goodson William H , Wood Douglas J , Henry Solomon , Rouse Robert V , Bailey Lisa , Philben Vicki J , Dirbas Frederick M , Dunn Jocelyn J , Johnson Denise L , Wapnir Irene L , Carlson Robert W , Stockdale Frank E , Hansen Nora M , Jeffrey Stefanie S ,   The Bay Area SLN Study
Published: March 2008

AbstractBackgroundCurrent practice is to perform a completion axillary lymph node dissection (ALND) for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs), although fewer than half will have non-sentinel node (NSLN) metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model.MethodsWe constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC), boosted Classification and Regression Trees (CART), and multivariate logistic regression (MLR) informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram) in our dataset and an independent dataset from Northwestern University.Results285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93%) patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%). 101 (35%) of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size) predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC) was 0.83/0.85 for MLR (n = 213/n = 171) and 0.77 for Nomogram (n = 171). When applied to an independent dataset (n = 77), AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of angiolymphatic invasion and size of SLN metastasis, and the product of tumor size and square of SLN metastasis size.ConclusionWe present a new model developed from a community-based SLN database that uses only three rather than eight variables to achieve higher accuracy than the Nomogram for predicting NSLN status in two different datasets.