Search for a platelet-activating factor receptor in the Trypanosoma cruzi proteome: a potential target for Chagas disease chemotherapy

Chagas disease (CD) causes the highest burden of parasitic diseases in the Western Hemisphere and is therefore a priority for drug research and development. Platelet-activating factor (PAF) causes the CD parasite Trypanosoma cruzi to differentiate, which suggests that the parasite may express PAF receptors. Here, we explored the T. cruzi proteome for PAF receptor-like proteins. From a total of 23,000 protein sequences, we identified 29 hypothetical proteins that are predicted to have seven transmembrane domains (TMDs), which is the main characteristic of the G protein-coupled receptors (GPCRs), including the PAF receptor. The TMDs of these sequences were independently aligned with domains from 25 animal PAF receptors and the sequences were analysed for conserved residues. The conservation score mean values for the TMDs of the hypothetical proteins ranged from 31.7-44.1%, which suggests that if the putative T. cruzi PAF receptor is among the sequences identified, the TMDs are not highly conserved. These results suggest that T. cruzi contains several GPCR-like proteins and that one of these GPCRs may be a PAF receptor. Future studies may further validate the PAF receptor as a target for CD chemotherapy.

Intelligent PCA contribution analysis for quality estimation in batch processes. Application in a sequencing batch reactor for wastewater treatment

En aquest treball, es proposa un nou mètode per estimar en temps real la qualitat del producte final en processos per lot. Aquest mètode permet reduir el temps necessari per obtenir els resultats de qualitat de les anàlisi de laboratori. S'utiliza un model de anàlisi de componentes principals (PCA) construït amb dades històriques en condicions normals de funcionament per discernir si un lot finalizat és normal o no. Es calcula una signatura de falla pels lots anormals i es passa a través d'un model de classificació per la seva estimació. L'estudi proposa un mètode per utilitzar la informació de les gràfiques de contribució basat en les signatures de falla, on els indicadors representen el comportament de les variables al llarg del procés en les diferentes etapes. Un conjunt de dades compost per la signatura de falla dels lots anormals històrics es construeix per cercar els patrons i entrenar els models de classifcació per estimar els resultas dels lots futurs. La metodologia proposada s'ha aplicat a un reactor seqüencial per lots (SBR). Diversos algoritmes de classificació es proven per demostrar les possibilitats de la metodologia proposada.

Comparison of topography- and aperture-dependent motion compensation algorithms for airborne SAR

This letter presents a comparison between threeFourier-based motion compensation (MoCo) algorithms forairborne synthetic aperture radar (SAR) systems. These algorithmscircumvent the limitations of conventional MoCo, namelythe assumption of a reference height and the beam-center approximation.All these approaches rely on the inherent time–frequencyrelation in SAR systems but exploit it differently, with the consequentdifferences in accuracy and computational burden. Aftera brief overview of the three approaches, the performance ofeach algorithm is analyzed with respect to azimuthal topographyaccommodation, angle accommodation, and maximum frequencyof track deviations with which the algorithm can cope. Also, ananalysis on the computational complexity is presented. Quantitativeresults are shown using real data acquired by the ExperimentalSAR system of the German Aerospace Center (DLR).

Identification of new MHC class I-restricted human tumor antigens for immunotherapy

Summary Cancer is a leading cause of morbidity and mortality in Western countries (as an example, colorectal cancer accounts for about 300'000 new cases and 200'000 deaths each year in Europe and in the USA). Despite that many patients with cancer have complete macroscopic clearance of their disease after resection, radiotherapy and/or chemotherapy, many of these patients develop fatal recurrence. Vaccination with immunogenic peptide tumor antigens has shown encouraging progresses in the last decade; immunotherapy might therefore constitute a fourth therapeutic option in the future. We dissect here and critically evaluate the numerous steps of reverse immunology, a forecast procedure to identify antigenic peptides from the sequence of a gene of interest. Bioinformatic algorithms were applied to mine sequence databases for tumor-specific transcripts. A quality assessment of publicly available sequence databanks allowed defining strengths and weaknesses of bioinformatics-based prediction of colon cancer-specific alternative splicing: new splice variants could be identified, however cancer-restricted expression could not be significantly predicted. Other sources of target transcripts were quantitatively investigated by polymerase chain reactions, as cancer-testis genes or reported overexpressed transcripts. Based on the relative expression of a defined set of housekeeping genes in colon cancer tissues, we characterized a precise procedure for accurate normalization and determined a threshold for the definition of significant overexpression of genes in cancers versus normal tissues. Further steps of reverse immunology were applied on a splice variant of the Melan¬A gene. Since it is known that the C-termini of antigenic peptides are directly produced by the proteasome, longer precursor and overlapping peptides encoded by the target sequence were synthesized chemically and digested in vitro with purified proteasome. The resulting fragments were identified by mass spectroscopy to detect cleavage sites. Using this information and based on the available anchor motifs for defined HLA class I molecules, putative antigenic peptides could be predicted. Their relative affinity for HLA molecules was confirmed experimentally with functional competitive binding assays and they were used to search patients' peripheral blood lymphocytes for the presence of specific cytolytic T lymphocytes (CTL). CTL clones specific for a splice variant of Melan-A could be isolated; although they recognized peptide-pulsed cells, they failed to lyse melanoma cells in functional assays of antigen recognition. In the conclusion, we discuss advantages and bottlenecks of reverse immunology and compare the technical aspects of this approach with the more classical procedure of direct immunology, a technique introduced by Boon and colleagues more than 10 years ago to successfully clone tumor antigens.

Route optimization and customization using real geographical data in Android mobile devices

Nowadays, there are several services and applications that allow users to locate and move to different tourist areas using a mobile device. These systems can be used either by internet or downloading an application in concrete places like a visitors centre. Although such applications are able to facilitate the location and the search for points of interest, in most cases, these services and applications do not meet the needs of each user. This paper aims to provide a solution by studying the main projects, services and applications, their routing algorithms and their treatment of the real geographical data in Android mobile devices, focusing on the data acquisition and treatment to improve the routing searches in off-line environments.

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

A genome-wide association search for type 2 diabetes genes in African Americans.

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.

Selection of Reference Genes for Quantitative Real Time PCR (qPCR) Assays in Tissue from Human Ascending Aorta.

Dilatation of the ascending aorta (AAD) is a prevalent aortopathy that occurs frequently associated with bicuspid aortic valve (BAV), the most common human congenital cardiac malformation. The molecular mechanisms leading to AAD associated with BAV are still poorly understood. The search for differentially expressed genes in diseased tissue by quantitative real-time PCR (qPCR) is an invaluable tool to fill this gap. However, studies dedicated to identify reference genes necessary for normalization of mRNA expression in aortic tissue are scarce. In this report, we evaluate the qPCR expression of six candidate reference genes in tissue from the ascending aorta of 52 patients with a variety of clinical and demographic characteristics, normal and dilated aortas, and different morphologies of the aortic valve (normal aorta and normal valve n = 30; dilated aorta and normal valve n = 10; normal aorta and BAV n = 4; dilated aorta and BAV n = 8). The expression stability of the candidate reference genes was determined with three statistical algorithms, GeNorm, NormFinder and Bestkeeper. The expression analyses showed that the most stable genes for the three algorithms employed were CDKN1β, POLR2A and CASC3, independently of the structure of the aorta and the valve morphology. In conclusion, we propose the use of these three genes as reference genes for mRNA expression analysis in human ascending aorta. However, we suggest searching for specific reference genes when conducting qPCR experiments with new cohort of samples.

Clustering algorithms for anti-money laundering using graph theory and social network analysis

HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Financial Institutes (Banks, Insurance Companies, etc.). This Master-Thesis project is done at AIA, one of the partners for the HEMOLIA project in Barcelona. The objective of this thesis is to find the clusters in a network drawn by using the financial data. An extensive literature survey has been carried out and several standard algorithms related to networks have been studied and implemented. The clustering problem is a NP-hard problem and several algorithms like K-Means and Hierarchical clustering are being implemented for studying several problems relating to sociology, evolution, anthropology etc. However, these algorithms have certain drawbacks which make them very difficult to implement. The thesis suggests (a) a possible improvement to the K-Means algorithm, (b) a novel approach to the clustering problem using the Genetic Algorithms and (c) a new algorithm for finding the cluster of a node using the Genetic Algorithm.

Multicast algorithms evaluation using an adaptative routing in ATM networks

This paper proposes a multicast implementation based on adaptive routing with anticipated calculation. Three different cost measures for a point-to-multipoint connection: bandwidth cost, connection establishment cost and switching cost can be considered. The application of the method based on pre-evaluated routing tables makes possible the reduction of bandwidth cost and connection establishment cost individually

New perspectives in the use of ink evidence in forensic science: Part II. Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC

In the first part of this research, three stages were stated for a program to increase the information extracted from ink evidence and maximise its usefulness to the criminal and civil justice system. These stages are (a) develop a standard methodology for analysing ink samples by high-performance thin layer chromatography (HPTLC) in reproducible way, when ink samples are analysed at different time, locations and by different examiners; (b) compare automatically and objectively ink samples; and (c) define and evaluate theoretical framework for the use of ink evidence in forensic context. This report focuses on the second of the three stages. Using the calibration and acquisition process described in the previous report, mathematical algorithms are proposed to automatically and objectively compare ink samples. The performances of these algorithms are systematically studied for various chemical and forensic conditions using standard performance tests commonly used in biometrics studies. The results show that different algorithms are best suited for different tasks. Finally, this report demonstrates how modern analytical and computer technology can be used in the field of ink examination and how tools developed and successfully applied in other fields of forensic science can help maximising its impact within the field of questioned documents.

Decision Support Methods for Global Optomization

Immobile location-allocation (LA) problems is a type of LA problem that consists in determining the service each facility should offer in order to optimize some criterion (like the global demand), given the positions of the facilities and the customers. Due to the complexity of the problem, i.e. it is a combinatorial problem (where is the number of possible services and the number of facilities) with a non-convex search space with several sub-optimums, traditional methods cannot be applied directly to optimize this problem. Thus we proposed the use of clustering analysis to convert the initial problem into several smaller sub-problems. By this way, we presented and analyzed the suitability of some clustering methods to partition the commented LA problem. Then we explored the use of some metaheuristic techniques such as genetic algorithms, simulated annealing or cuckoo search in order to solve the sub-problems after the clustering analysis

When should clinicians search for GLUT1 deficiency syndrome in childhood generalized epilepsies?

UNLABELLED: GLUT1 deficiency (GLUT1D) has recently been identified as an important cause of generalized epilepsies in childhood. As it is a treatable condition, it is crucial to determine which patients should be investigated. METHODS: We analyzed SLC2A1 for mutations in a group of 93 unrelated children with generalized epilepsies. Fasting lumbar puncture was performed following the identification of a mutation. We compared our results with a systematic review of 7 publications of series of patients with generalized epilepsies screened for SLC2A1 mutations. RESULTS: We found 2/93 (2.1%) patients with a SLC2A1 mutation. One, carrying a novel de novo deletion had epilepsy with myoclonic-atonic seizures (MAE), mild slowing of head growth, choreiform movements and developmental delay. The other, with a paternally inherited missense mutation, had childhood absence epilepsy with atypical EEG features and paroxysmal exercise-induced dyskinesia (PED) initially misdiagnosed as myoclonic seizures. Out of a total of 1110 screened patients with generalized epilepsies from 7 studies, 2.4% (29/1110) had GLUT1D. This rate was higher (5.6%) among 303 patients with early onset absence epilepsy (EOAE) from 4 studies. About 50% of GLUT1D patients had abnormal movements and 41% a family history of seizures, abnormal movements or both. CONCLUSION: GLUT1D is most likely to be found in MAE and in EOAE. The probability of finding GLUT1D in the classical idiopathic generalized epilepsies is very low. Pointers to GLUT1D include an increase in seizures before meals, cognitive impairment, or PED which can easily be overlooked.

Implementation of zonal control algorithms in adaptive optical systems with sparse control matrices

Miralls deformables més i més grans, amb cada cop més actuadors estan sent utilitzats actualment en aplicacions d'òptica adaptativa. El control dels miralls amb centenars d'actuadors és un tema de gran interès, ja que les tècniques de control clàssiques basades en la seudoinversa de la matriu de control del sistema es tornen massa lentes quan es tracta de matrius de dimensions tan grans. En aquesta tesi doctoral es proposa un mètode per l'acceleració i la paral.lelitzacó dels algoritmes de control d'aquests miralls, a través de l'aplicació d'una tècnica de control basada en la reducció a zero del components més petits de la matriu de control (sparsification), seguida de l'optimització de l'ordenació dels accionadors de comandament atenent d'acord a la forma de la matriu, i finalment de la seva posterior divisió en petits blocs tridiagonals. Aquests blocs són molt més petits i més fàcils de fer servir en els càlculs, el que permet velocitats de càlcul molt superiors per l'eliminació dels components nuls en la matriu de control. A més, aquest enfocament permet la paral.lelització del càlcul, donant una com0onent de velocitat addicional al sistema. Fins i tot sense paral. lelització, s'ha obtingut un augment de gairebé un 40% de la velocitat de convergència dels miralls amb només 37 actuadors, mitjançant la tècnica proposada. Per validar això, s'ha implementat un muntatge experimental nou complet , que inclou un modulador de fase programable per a la generació de turbulència mitjançant pantalles de fase, i s'ha desenvolupat un model complert del bucle de control per investigar el rendiment de l'algorisme proposat. Els resultats, tant en la simulació com experimentalment, mostren l'equivalència total en els valors de desviació després de la compensació dels diferents tipus d'aberracions per als diferents algoritmes utilitzats, encara que el mètode proposat aquí permet una càrrega computacional molt menor. El procediment s'espera que sigui molt exitós quan s'aplica a miralls molt grans.