On optimal computation of MPLS label binding for multipoint-to-point connections

Most network operators have considered reducing Label Switched Routers (LSR) label spaces (i.e. the number of labels that can be used) as a means of simplifying management of underlaying Virtual Private Networks (VPNs) and, hence, reducing operational expenditure (OPEX). This letter discusses the problem of reducing the label spaces in Multiprotocol Label Switched (MPLS) networks using label merging - better known as MultiPoint-to-Point (MP2P) connections. Because of its origins in IP, MP2P connections have been considered to have tree- shapes with Label Switched Paths (LSP) as branches. Due to this fact, previous works by many authors affirm that the problem of minimizing the label space using MP2P in MPLS - the Merging Problem - cannot be solved optimally with a polynomial algorithm (NP-complete), since it involves a hard- decision problem. However, in this letter, the Merging Problem is analyzed, from the perspective of MPLS, and it is deduced that tree-shapes in MP2P connections are irrelevant. By overriding this tree-shape consideration, it is possible to perform label merging in polynomial time. Based on how MPLS signaling works, this letter proposes an algorithm to compute the minimum number of labels using label merging: the Full Label Merging algorithm. As conclusion, we reclassify the Merging Problem as Polynomial-solvable, instead of NP-complete. In addition, simulation experiments confirm that without the tree-branch selection problem, more labels can be reduced

Spatial distribution of Schistosoma mansoni infection before and after chemotherapy with two praziquantel doses in a community of Pernambuco, Brazil

Praziquantel chemotherapy has been the focus of the Schistosomiasis Control Program in Brazil for the past two decades. Nevertheless, information on the impact of selective chemotherapy against Schistosoma mansoni infection under the conditions confronted by the health teams in endemic municipalities remains scarce. This paper compares the spatial pattern of infection before and after treatment with either a 40 mg/kg or 60 mg/kg dose of praziquantel by determining the intensity of spatial cluster among patients at 180 and 360 days after treatment. The spatial-temporal distribution of egg-positive patients was analysed in a Geographic Information System using the kernel smoothing technique. While all patients became egg-negative after 21 days, 17.9% and 30.9% reverted to an egg-positive condition after 180 and 360 days, respectively. Both the prevalence and intensity of infection after treatment were significantly lower in the 60 mg/kg than in the 40 mg/kg treatment group. The higher intensity of the kernel in the 40 mg/kg group compared to the 60 mg/kg group, at both 180 and 360 days, reflects the higher number of reverted cases in the lower dose group. Auxiliary, preventive measures to control transmission should be integrated with chemotherapy to achieve a more enduring impact.

The RNA-binding protein HuR regulates DNA methylation through stabilization of DNMT3b mRNA

The molecular basis underlying the aberrant DNA-methylation patterns in human cancer is largely unknown. Altered DNA methyltransferase (DNMT) activity is believed to contribute, as DNMT expression levels increase during tumorigenesis. Here, we present evidence that the expression of DNMT3b is post-transcriptionally regulated by HuR, an RNA-binding protein that stabilizes and/or modulates the translation of target mRNAs. The presence of a putative HuR-recognition motif in the DNMT3b 3'UTR prompted studies to investigate if this transcript associated with HuR. The interaction between HuR and DNMT3b mRNA was studied by immunoprecipitation of endogenous HuR ribonucleoprotein complexes followed by RT-qPCR detection of DNMT3b mRNA, and by in vitro pulldown of biotinylated DNMT3b RNAs followed by western blotting detection of HuR. These studies revealed that binding of HuR stabilized the DNMT3b mRNA and increased DNMT3b expression. Unexpectedly, cisplatin treatment triggered the dissociation of the [HuR-DNMT3b mRNA] complex, in turn promoting DNMT3b mRNA decay, decreasing DNMT3b abundance, and lowering the methylation of repeated sequences and global DNA methylation. In summary, our data identify DNMT3b mRNA as a novel HuR target, present evidence that HuR affects DNMT3b expression levels post-transcriptionally, and reveal the functional consequences of the HuR-regulated DNMT3b upon DNA methylation patterns.

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S-SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient.Location Two study areas in the Alps of Switzerland.Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways - summing binary predictions, summing random draws of binomial trials and summing predicted probabilities - to obtain a final species count.Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S-SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump-shaped pattern of SR observed along the elevational gradient. The S-SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S-SDM approaches the summed binomial trials based on predicted probabilities and summed predicted probabilities - do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S-SDM approaches fail to appropriately reproduce the observed hump-shaped patterns of SR along the elevational gradient.Main conclusions Macroecological approach and S-SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S-SDM by MEM predictions.

Remorin, a uronide binding protein with physical properties similar to the tobacco mosaic virus movement protein

The extracellular pectic matrix is a rich source of oligogalacturonic acid (OGA), one of the most abundant polymeric regulatory molecules on the earth's surface. OGAs regulate the expression of a variety of defense genes and have also been implicated in developmental processes. Little is known about how cells perceive OGAs and we have been attempting to characterise proteins capable of interacting with these molecules. We recently succeeded in cloning a cDNA encoding a small OGA-binding protein, remorin. OGA-binding to remorin is not highly specific, the protein binds homogalacturonides, complex pectic polymers and the animal polyuronide heparin. This lack of specificity contrasts with that often observed with classical receptors and the function of remorin remains to be discovered. Remorin copurifies with the plasma membrane but is a very hydrophilic polypeptide. Its behavior during cell fractionation, as well as a number of properties including the OGA-stimulated in vitro phosphorylation and preliminary localization studies, all suggest parallels with some viral movement proteins. Some of these comparisons will be presented. Experiments to directly test for the possible role of this protein in cell-to-cell signalling are in progress. EEF is supported by FNRS grant 31-3672-92.

Cluster recognition in spatial-temporal sequences: The case of forest fires

Forest fire sequences can be modelled as a stochastic point process where events are characterized by their spatial locations and occurrence in time. Cluster analysis permits the detection of the space/time pattern distribution of forest fires. These analyses are useful to assist fire-managers in identifying risk areas, implementing preventive measures and conducting strategies for an efficient distribution of the firefighting resources. This paper aims to identify hot spots in forest fire sequences by means of the space-time scan statistics permutation model (STSSP) and a geographical information system (GIS) for data and results visualization. The scan statistical methodology uses a scanning window, which moves across space and time, detecting local excesses of events in specific areas over a certain period of time. Finally, the statistical significance of each cluster is evaluated through Monte Carlo hypothesis testing. The case study is the forest fires registered by the Forest Service in Canton Ticino (Switzerland) from 1969 to 2008. This dataset consists of geo-referenced single events including the location of the ignition points and additional information. The data were aggregated into three sub-periods (considering important preventive legal dispositions) and two main ignition-causes (lightning and anthropogenic causes). Results revealed that forest fire events in Ticino are mainly clustered in the southern region where most of the population is settled. Our analysis uncovered local hot spots arising from extemporaneous arson activities. Results regarding the naturally-caused fires (lightning fires) disclosed two clusters detected in the northern mountainous area.

Binding of ²³⁹Pu and ⁹⁰Sr to organic colloids in soil solutions: evidence from a field experiment.

Colloidal transport has been shown to enhance the migration of plutonium in groundwater downstream from contaminated sites, but little is known about the adsorption of ⁹⁰Sr and plutonium onto colloids in the soil solution of natural soils. We sampled soil solutions using suction cups, and separated colloids using ultrafiltration to determine the distribution of ²³⁹Pu and ⁹⁰Sr between the truly dissolved fraction and the colloidal fraction of the solutions of three Alpine soils contaminated only by global fallout from the nuclear weapon tests. Plutonium was essentially found in the colloidal fraction (>80%) and probably associated with organic matter. A significant amount of colloidal ⁹⁰Sr was detected in organic-rich soil solutions. Our results suggest that binding to organic colloids in the soil solutions plays a key role with respect to the mobility of plutonium in natural alpine soils and, to a lesser extent, to the mobility of ⁹⁰Sr.

Aggravation of chronic stress effects on hippocampal neurogenesis and spatial memory in LPA₁ receptor knockout mice.

BACKGROUND The lysophosphatidic acid LPA₁ receptor regulates plasticity and neurogenesis in the adult hippocampus. Here, we studied whether absence of the LPA₁ receptor modulated the detrimental effects of chronic stress on hippocampal neurogenesis and spatial memory. METHODOLOGY/PRINCIPAL FINDINGS Male LPA₁-null (NULL) and wild-type (WT) mice were assigned to control or chronic stress conditions (21 days of restraint, 3 h/day). Immunohistochemistry for bromodeoxyuridine and endogenous markers was performed to examine hippocampal cell proliferation, survival, number and maturation of young neurons, hippocampal structure and apoptosis in the hippocampus. Corticosterone levels were measured in another a separate cohort of mice. Finally, the hole-board test assessed spatial reference and working memory. Under control conditions, NULL mice showed reduced cell proliferation, a defective population of young neurons, reduced hippocampal volume and moderate spatial memory deficits. However, the primary result is that chronic stress impaired hippocampal neurogenesis in NULLs more severely than in WT mice in terms of cell proliferation; apoptosis; the number and maturation of young neurons; and both the volume and neuronal density in the granular zone. Only stressed NULLs presented hypocortisolemia. Moreover, a dramatic deficit in spatial reference memory consolidation was observed in chronically stressed NULL mice, which was in contrast to the minor effect observed in stressed WT mice. CONCLUSIONS/SIGNIFICANCE These results reveal that the absence of the LPA₁ receptor aggravates the chronic stress-induced impairment to hippocampal neurogenesis and its dependent functions. Thus, modulation of the LPA₁ receptor pathway may be of interest with respect to the treatment of stress-induced hippocampal pathology.

Predicting spatial patterns of plant biodiversity : from species to communities

Understanding the distribution and composition of species assemblages and being able to predict them in space and time are highly important tasks io investigate the fate of biodiversity in the current global changes context. Species distribution models are tools that have proven useful to predict the potential distribution of species by relating their occurrences to environmental variables. Species assemblages can then be predicted by combining the prediction of individual species models. In the first part of my thesis, I tested the importance of new environmental predictors to improve species distribution prediction. I showed that edaphic variables, above all soil pH and nitrogen content could be important in species distribution models. In a second chapter, I tested the influence of different resolution of predictors on the predictive ability of species distribution models. I showed that fine resolution predictors could ameliorate the models for some species by giving a better estimation of the micro-topographic condition that species tolerate, but that fine resolution predictors for climatic factors still need to be ameliorated. The second goal of my thesis was to test the ability of empirical models to predict species assemblages' characteristics such as species richness or functional attributes. I showed that species richness could be modelled efficiently and that the resulting prediction gave a more realistic estimate of the number of species than when obtaining it by stacking outputs of single species distribution models. Regarding the prediction of functional characteristics (plant height, leaf surface, seed mass) of plant assemblages, mean and extreme values of functional traits were better predictable than indices reflecting the diversity of traits in the community. This approach proved interesting to understand which environmental conditions influence particular aspects of the vegetation functioning. It could also be useful to predict climate change impacts on the vegetation. In the last part of my thesis, I studied the capacity of stacked species distribution models to predict the plant assemblages. I showed that this method tended to over-predict the number of species and that the composition of the community was not predicted exactly either. Finally, I combined the results of macro- ecological models obtained in the preceding chapters with stacked species distribution models and showed that this approach reduced significantly the number of species predicted and that the prediction of the composition is also ameliorated in some cases. These results showed that this method is promising. It needs now to be tested on further data sets. - Comprendre la manière dont les plantes se répartissent dans l'environnement et s'organisent en communauté est une question primordiale dans le contexte actuel de changements globaux. Cette connaissance peut nous aider à sauvegarder la diversité des espèces et les écosystèmes. Des méthodes statistiques nous permettent de prédire la distribution des espèces de plantes dans l'espace géographique et dans le temps. Ces modèles de distribution d'espèces, relient les occurrences d'une espèce avec des variables environnementales pour décrire sa distribution potentielle. Cette méthode a fait ses preuves pour ce qui est de la prédiction d'espèces individuelles. Plus récemment plusieurs tentatives de cumul de modèles d'espèces individuelles ont été réalisées afin de prédire la composition des communautés végétales. Le premier objectif de mon travail est d'améliorer les modèles de distribution en testant l'importance de nouvelles variables prédictives. Parmi différentes variables édaphiques, le pH et la teneur en azote du sol se sont avérés des facteurs non négligeables pour prédire la distribution des plantes. Je démontre aussi dans un second chapitre que les prédicteurs environnementaux à fine résolution permettent de refléter les conditions micro-topographiques subies par les plantes mais qu'ils doivent encore être améliorés avant de pouvoir être employés de manière efficace dans les modèles. Le deuxième objectif de ce travail consistait à étudier le développement de modèles prédictifs pour des attributs des communautés végétales tels que, par exemple, la richesse en espèces rencontrée à chaque point. Je démontre qu'il est possible de prédire par ce biais des valeurs de richesse spécifiques plus réalistes qu'en sommant les prédictions obtenues précédemment pour des espèces individuelles. J'ai également prédit dans l'espace et dans le temps des caractéristiques de la végétation telles que sa hauteur moyenne, minimale et maximale. Cette approche peut être utile pour comprendre quels facteurs environnementaux promeuvent différents types de végétation ainsi que pour évaluer les changements à attendre au niveau de la végétation dans le futur sous différents régimes de changements climatiques. Dans une troisième partie de ma thèse, j'ai exploré la possibilité de prédire les assemblages de plantes premièrement en cumulant les prédictions obtenues à partir de modèles individuels pour chaque espèce. Cette méthode a le défaut de prédire trop d'espèces par rapport à ce qui est observé en réalité. J'ai finalement employé le modèle de richesse en espèce développé précédemment pour contraindre les résultats du modèle d'assemblage de plantes. Cela a permis l'amélioration des modèles en réduisant la sur-prédiction et en améliorant la prédiction de la composition en espèces. Cette méthode semble prometteuse mais de nouveaux tests sont nécessaires pour bien évaluer ses capacités.

Reassessing the role of Staphylococcus aureus clumping factor and fibronectin-binding protein by expression in Lactococcus lactis.

Since Staphylococcus aureus expresses multiple pathogenic factors, studying their individual roles in single-gene-knockout mutants is difficult. To circumvent this problem, S. aureus clumping factor A (clfA) and fibronectin-binding protein A (fnbA) genes were constitutively expressed in poorly pathogenic Lactococcus lactis using the recently described pOri23 vector. The recombinant organisms were tested in vitro for their adherence to immobilized fibrinogen and fibronectin and in vivo for their ability to infect rats with catheter-induced aortic vegetations. In vitro, both clfA and fnbA increased the adherence of lactococci to their specific ligands to a similar extent as the S. aureus gene donor. In vivo, the minimum inoculum size producing endocarditis in > or =80% of the rats (80% infective dose [ID80]) with the parent lactococcus was > or =10(7) CFU. In contrast, clfA-expressing and fnbA-expressing lactococci required only 10(5) CFU to infect the majority of the animals (P < 0.00005). This was comparable to the infectivities of classical endocarditis pathogens such as S. aureus and streptococci (ID80 = 10(4) to 10(5) CFU) in this model. The results confirmed the role of clfA in endovascular infection, but with a much higher degree of confidence than with single-gene-inactivated staphylococci. Moreover, they identified fnbA as a critical virulence factor of equivalent importance. This was in contrast to previous studies that produced controversial results regarding this very determinant. Taken together, the present observations suggest that if antiadhesin therapy were to be developed, at least both of the clfA and fnbA products should be blocked for the therapy to be effective.

Characterization and binding affinities of SmLANP: a new Schistosoma mansoni member of the ANP32 family of regulatory proteins.

Members of the leucine-rich repeat protein family are involved in diverse functions including protein phosphatase 2-inhibition, cell cycle regulation, gene regulation and signalling pathways. A novel Schistosoma mansoni gene, called SmLANP, presenting homology to various genes coding for proteins that belong to the super family of leucine-rich repeat proteins, was characterized here. SmLANP was 1184bp in length as determined from cDNA and genomic sequences and encoded a 296 amino acid open reading frame that spanning from 6 to 894bp. The predicted amino acid sequence had a calculated molecular weight of 32kDa. Analysis of the predicted sequence indicated the presence of 3 leucine-rich domains (LRR) located in the N-terminal region and an aspartic acid rich region in the C-terminal end. SmLANP transcript is expressed in all stages of the S. mansoni life cycle analyzed, exhibiting the highest expression level in males. The SmLANP protein was expressed in a GST expression system and antibodies raised in mice against the recombinant protein. By immunolocalization assay, using adult worms, it was shown that the protein is mainly present in the cell nucleus through the whole body and strongly expressed along the tegument cell body nuclei of adult worms. As members of this family are usually involved in protein-protein interaction, a yeast two hybrid assay was conducted to identify putative binding partners for SmLANP. Thirty-six possible partners were identified, and a protein ATP synthase subunit alpha was confirmed by pull down assays, as a binding partner of the SmLANP protein.

Gene transfer of interleukin-18-binding protein attenuates cardiac allograft rejection.

Interleukin (IL) 18 is a potent pro-inflammatory Th1 cytokine that exerts pleiotropic effector functions in both innate and acquired immune responses. Increased IL-18 production during acute rejection has been reported in experimental heart transplantation models and in kidney transplant recipients. IL-18-binding protein (IL-18BP) binds IL-18 with high affinity and neutralizes its biologic activity. We have analyzed the efficacy of an adenoviral vector expressing an IL-18BP-Ig fusion protein in a rat model of heart transplantation. IL-18BP-Ig gene transfer into Fisher (F344) rat donor hearts resulted in prolonged graft survival in Lewis recipients (15.8 +/- 1.4 days vs. 10.3 +/- 2.5 and 10.1 +/- 2.1 days with control virus and buffer solution alone, respectively; P < 0.001). Immunohistochemical analysis revealed decreased intra-graft infiltrates of monocytes/macrophages, CD4(+), CD8alpha(+) and T-cell receptor alphabeta(+) cells after IL-18BP-Ig versus mock gene transfer (P < 0.05). Real-time reverse transcriptase polymerase chain reaction analysis showed decreased cytokine transcripts for the RANTES chemokine and transforming growth factor-beta after IL-18BP-Ig gene transfer (P < 0.05). IL-18BP-Ig gene transfer attenuates inflammatory cell infiltrates and prolongs cardiac allograft survival in rats. These results suggest a contributory role for IL-18 in acute rejection. Further studies aiming at defining the therapeutic potential of IL-18BP are warranted.

Common variants of the liver fatty acid binding protein gene influence the risk of type 2 diabetes and insulin resistance in Spanish population

SUMMARY The main objective was to evaluate the association between SNPs and haplotypes of the FABP1-4 genes and type 2 diabetes, as well as its interaction with fat intake, in one general Spanish population. The association was replicated in a second population in which HOMA index was also evaluated. METHODS 1217 unrelated individuals were selected from a population-based study [Hortega study: 605 women; mean age 54 y; 7.8% with type 2 diabetes]. The replication population included 805 subjects from Segovia, a neighboring region of Spain (446 females; mean age 52 y; 10.3% with type 2 diabetes). DM2 mellitus was defined in a similar way in both studies. Fifteen SNPs previously associated with metabolic traits or with potential influence in the gene expression within the FABP1-4 genes were genotyped with SNPlex and tested. Age, sex and BMI were used as covariates in the logistic regression model. RESULTS One polymorphism (rs2197076) and two haplotypes of the FABP-1 showed a strong association with the risk of DM2 in the original population. This association was further confirmed in the second population as well as in the pooled sample. None of the other analyzed variants in FABP2, FABP3 and FABP4 genes were associated. There was not a formal interaction between rs2197076 and fat intake. A significant association between the rs2197076 and the haplotypes of the FABP1 and HOMA-IR was also present in the replication population. CONCLUSIONS The study supports the role of common variants of the FABP-1 gene in the development of type 2 diabetes in Caucasians.