866 resultados para Package inserts of medicines
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In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.
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This paper describes methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way.
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Research has shown that one of the major contributing factors in early joint deterioration of portland cement concrete (PCC) pavement is the quality of the coarse aggregate. Conventional physical and freeze/thaw tests are slow and not satisfactory in evaluating aggregate quality. In the last ten years the Iowa DOT has been evaluating X-ray analysis and other new technologies to predict aggregate durability in PCC pavement. The objective of this research is to evaluate thermogravimetric analysis (TGA) of carbonate aggregate. The TGA testing has been conducted with a TA 2950 Thermogravimetric Analyzer. The equipment is controlled by an IBM compatible computer. A "TA Hi-RES" (trademark) software package allows for rapid testing while retaining high resolution. The carbon dioxide is driven off the dolomite fraction between 705 deg C and 745 deg C and off the calcite fraction between 905 deg C and 940 deg C. The graphical plot of the temperature and weight loss using the same sample size and test procedure demonstrates that the test is very accurate and repeatable. A substantial number of both dolomites and limestones (calcites) have been subjected to TGA testing. The slopes of the weight loss plot prior to the dolomite and calcite transitions does correlate with field performance. The noncarbonate fraction, which correlates to the acid insolubles, can be determined by TGA for most calcites and some dolomites. TGA has provided information that can be used to help predict the quality of carbonate aggregate.
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The objective of this work was to study the fruit compression behavior aiming to develop new tomato packages. Deformations caused by compression forces were observed inside packages and in individual 'Santa Clara' tomato fruit. The forces applied by a transparent acrylic lever to the fruit surface caused pericarp deformation and the flattened area was proportional to the force magnitude. The deformation was associated to the reduction in the gas volume (Vg), caused by expulsion of the air from the loculus cavity and reduction in the intercellular air volume of the pericarp. As ripening advanced, smaller fractions of the Vg reduced by the compressive force were restored after the stress was relieved. The lack of complete Vg restoration was an indication of permanent plastic deformations of the stressed cells. Vg regeneration (elastic recovery) was larger in green fruits than in the red ones. The ratio between the applied force and the flattened area (flattening pressure), which depends on cell turgidity, decreased during ripening. Fruit movements associated with its depth in the container were observed during storage in a transparent glass container (495 x 355 x 220 mm). The downward movement of the fruits was larger in the top layers because these movements seem to be driven by a summation of the deformation of many fruits in all layers.
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Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions
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Background and objective: Asthma is one of the most frequent chronic diseases affecting children and adolescents. Good compliance is indispensable for effective treatment since a suboptimal use of inhalation devices can result in decreased therapeutic efficacy and increased morbidity. The objective of this work was to evaluate the inhalation technique of paediatric patients visiting a specialized consultation clinic of a university hospital. Design: Observational prospective study during a 3-month period. Setting Specialized consultation clinic of a university hospital. Main outcome measures: This study involved 40 outpatient infants, children and adolescents visiting alone or with their parent(s). Patients' data (age, sex, weight, diagnostic, reason for consulting, previous consultations) and their medicines were compiled using an ad hoc form. Filmed sequences of the inhalation procedure used by each child were reviewed independently by members of an interdisciplinary team consisting in a physician, a pharmacist, a nurse and a physiotherapist. A score of 1 was assigned to each correct step in the procedure, and a score of 0 to an incorrect step. A perfect procedure implied 12 correct steps. Results: Thirty patients were treated with a metered-dose inhaler and an inhalation chamber (Babyhaler or AeroChamber Plus); ten other patients were treated with a dry powder inhaler (Diskus or Turbuhaler). The agreement between the members of the interdisciplinary team was considered satisfactory. Nine patients (22.5%) reached an average score lower than 7, 18 patients (45%) a score between 7 and 10 and 13 (32.5%) a score equal to or better than 10. No patient reached the maximum score of 12. Users of the metered-dose inhalers (average score = 9.2) showed a better technique than users of the dry powder inhalers (average score = 7.4). Disappointingly, the score was not improved during a second consultation or following regular consultations. Conclusions: Video recording is a simple method to evaluate the degree of mastery of an inhalation procedure in paediatric patients. The method allows a convenient and efficient identification of suboptimal procedure steps by the hospital staff, and opens the way to patient-specific teaching. In two-thirds of juvenile patients, their inhalation technique was suboptimal despite initial training. This study shows conclusively that the inhalation technique in paediatric patients must be monitored during each examination, and teaching measures taken to improve it when necessary.
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During the past decades, anticancer immunotherapy has evolved from a promising therapeutic option to a robust clinical reality. Many immunotherapeutic regimens are now approved by the US Food and Drug Administration and the European Medicines Agency for use in cancer patients, and many others are being investigated as standalone therapeutic interventions or combined with conventional treatments in clinical studies. Immunotherapies may be subdivided into "passive" and "active" based on their ability to engage the host immune system against cancer. Since the anticancer activity of most passive immunotherapeutics (including tumor-targeting monoclonal antibodies) also relies on the host immune system, this classification does not properly reflect the complexity of the drug-host-tumor interaction. Alternatively, anticancer immunotherapeutics can be classified according to their antigen specificity. While some immunotherapies specifically target one (or a few) defined tumor-associated antigen(s), others operate in a relatively non-specific manner and boost natural or therapy-elicited anticancer immune responses of unknown and often broad specificity. Here, we propose a critical, integrated classification of anticancer immunotherapies and discuss the clinical relevance of these approaches.
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BACKGROUND: The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). METHODS: Seven cell lines representative of different types of cancer, including colon cancer (HT29 and Caco2), breast cancer (MCF-7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. Genes deregulated in common between the different cancer cell lines served to generate biological association networks using the Pathway Architect software. RESULTS: Dikkopf homolog-1 (DKK1) is a highly interconnected node in the network generated with genes in common between the two colon cancer cell lines, and functional validations of this target using small interfering RNAs (siRNAs) showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of genes differentially expressed in the two breast cancer cell lines. siRNA treatment against UGT1A also showed an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was overexpressed among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. CONCLUSIONS: Biological association networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using siRNA technology against these three genes showed chemosensitization toward MTX.
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The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.
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Résumé La thématique de cette thèse peut être résumée par le célèbre paradoxe de biologie évolutive sur le maintien du polymorphisme face à la sélection et par l'équation du changement de fréquence gamétique au cours du temps dû, à la sélection. La fréquence d'un gamète xi à la génération (t + 1) est: !!!Equation tronquée!!! Cette équation est utilisée pour générer des données utlisée tout au long de ce travail pour 2, 3 et 4 locus dialléliques. Le potentiel de l'avantage de l'hétérozygote pour le maintien du polymorphisme est le sujet de la première partie. La définition commune de l'avantage de l'hétérozygote n'etant applicable qu'a un locus ayant 2 allèles, cet avantage est redéfini pour un système multilocus sur les bases de précédentes études. En utilisant 5 définitions différentes de l'avantage de l'hétérozygote, je montre que cet avantage ne peut être un mécanisme général dans le maintien du polymorphisme sous sélection. L'étude de l'influence de locus non-détectés sur les processus évolutifs, seconde partie de cette thèse, est motivée par les travaux moléculaires ayant pour but de découvrir le nombre de locus codant pour un trait. La plupart de ces études sous-estiment le nombre de locus. Je montre que des locus non-détectés augmentent la probabilité d'observer du polymorphisme sous sélection. De plus, les conclusions sur les facteurs de maintien du polymorphisme peuvent être trompeuses si tous les locus ne sont pas détectés. Dans la troisième partie, je m'intéresse à la valeur attendue de variance additive après un goulot d'étranglement pour des traits sélectionés. Une études précédente montre que le niveau de variance additive après goulot d'étranglement augmente avec le nombre de loci. Je montre que le niveau de variance additive après un goulot d'étranglement augmente (comparé à des traits neutres), mais indépendamment du nombre de loci. Par contre, le taux de recombinaison a une forte influence, entre autre en regénérant les gamètes disparus suite au goulot d'étranglement. La dernière partie de ce travail de thèse décrit un programme pour le logiciel de statistique R. Ce programme permet d'itérer l'équation ci-dessus en variant les paramètres de sélection, recombinaison et de taille de populations pour 2, 3 et 4 locus dialléliques. Cette thèse montre qu'utiliser un système multilocus permet d'obtenir des résultats non-conformes à ceux issus de systèmes rnonolocus (la référence en génétique des populations). Ce programme ouvre donc d'intéressantes perspectives en génétique des populations. Abstract The subject of this PhD thesis can be summarized by one famous paradox of evolu-tionary biology: the maintenance of polymorphism in the face of selection, and one classical equation of theoretical population genetics: the changes in gametic frequencies due to selection and recombination. The frequency of gamete xi at generation (t + 1) is given by: !!! Truncated equation!!! This equation is used to generate data on selection at two, three, and four diallelic loci for the different parts of this work. The first part focuses on the potential of heterozygote advantage to maintain genetic polymorphism. Results of previous studies are used to (re)define heterozygote advantage for multilocus systems, since the classical definition is for one diallelic locus. I use 5 different definitions of heterozygote advantage. And for these five definitions, I show that heterozygote advantage is not a general mechanism for the maintenance of polymorphism. The study of the influence of undetected loci on evolutionary processes (second part of this work) is motivated by molecular works which aim at discovering the loci coding for a trait. For most of these works, some coding loci remains undetected. I show that undetected loci increases the probability of maintaining polymorphism under selection. In addition, conclusions about the factor that maintain polymorphism can be misleading if not all loci are considered. This is, therefore, only when all loci are detected that exact conclusions on the level of maintained polymorphism or on the factor(s) that maintain(s) polymorphism could be drawn. In the third part, the focus is on the expected release of additive genetic variance after bottleneck for selected traits. A previous study shows that the expected release of additive variance increases with an increase in the number of loci. I show that the expected release of additive variance after bottleneck increases for selected traits (compared with neutral), but this increase is not a function of the number of loci, but function of the recombination rate. Finally, the last part of this PhD thesis is a description of a package for the statistical software R that implements the Equation given above. It allows to generate data for different scenario regarding selection, recombination, and population size. This package opens perspectives for the theoretical population genetics that mainly focuses on one locus, while this work shows that increasing the number of loci leads not necessarily to straightforward results.
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The purpose of this work was to develop and optimize a simple and suitable method to detect the potential inhibitory effect of drugs and medicines on alcohol dehydrogenase (ADH) activity in order to evaluate the possible interactions between medicines and alcohol metabolism. Commonly used medicines that are often involved in court litigations related with driving under the influence of alcohol were selected. Alprazolam, flunitrazepam and tramadol were tested as drugs with no known effect on ADH activity. Cimetidine, reported previously as having inhibitory effect on ADH, and 4-methylpyrazole (4-MP), a well known ADH inhibitor, were tested as positive controls. Apart from 4-MP, tramadol was identified as having the higher inhibitory effect with an IC50 of 44.7×10(-3)mM, followed by cimetidine (IC50 of 122.9×10(-3)mM). Alprazolam and flunitrazepam also reduced liver ADH activity but to a smaller extent (inhibition of 11.8±5.0% for alprazolam 1.0mM and 34.5±7.1% for flunitrazepam 0.04mM). Apart from cimetidine, this is the first report describing the inhibitory effect of these drugs on ethanol metabolism. The results also show the suitability of the method to screen for inhibitory effect of drugs on ethanol metabolism helping to identify drugs for which further study is justified.
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3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.
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The bacterial microbiota from the whole gut of soldier and worker castes of the termite Reticulitermes grassei was isolated and studied. In addition, the 16S rDNA bacterial genes from gut DNA were PCR-amplified using Bacteria-selective primers, and the 16S rDNA amplicons subsequently cloned into Escherichia coli. Sequences of the cloned inserts were then used to determine closest relatives by comparison with published sequences and with sequences from our previous work. The clones were found to be affiliated with the phyla Spirochaetes, Proteobacteria, Firmicutes, Bacteroidetes, Actinobacteria, Synergistetes, Verrucomicrobia, and candidate phyla Termite Group 1 (TG1) and Termite Group 2 (TG2). No significant differences were observed with respect to the relative bacterial abundances between soldier and worker phylotypes. The phylotypes obtained in this study were compared with reported sequences from other termites, especially those of phylotypes related to Spirochaetes, Wolbachia (an Alphaproteobacteria), Actinobacteria, and TG1. Many of the clone phylotypes detected in soldiers grouped with those of workers. Moreover, clones CRgS91 (soldiers) and CRgW68 (workers), both affiliated with"Endomicrobia", were the same phylotype. Soldiers and workers also seemed to have similar relative protist abundances. Heterotrophic, poly-β-hydroxyalkanoate-accumulating bacteria were isolated from the gut of soldiers and shown to be affiliated with Actinobacteria and Gammaproteobacteria. We noted that Wolbachia was detected in soldiers but not in workers. Overall, the maintenance by soldiers and workers of comparable axial and radial redox gradients in the gut is consistent with the similarities in the prokaryotes and protists comprising their microbiota.
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While the E. coli RecA protein has been the most intensively studied enzyme of homologous recombination, the unusual RecA-DNA filament has stood alone until very recently. It now appears that this protein is part of a universal family that spans all of biology, and the filament that is formed by the protein on DNA is a universal structure. With RecA's role in recombination given new and greatly increased significance, we focus in this review on the energetics of the RecA-mediated strand exchange and the relation between the energetics and recombination spanning heterologous inserts.
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OBJECTIVES: Polypharmacy is one of the main management issues in public health policies because of its financial impact and the increasing number of people involved. The polymedicated population according to their demographic and therapeutic profile and the cost for the public healthcare system were characterised. DESIGN: Cross-sectional study. SETTING: Primary healthcare in Barcelona Health Region, Catalonia, Spain (5 105 551 inhabitants registered). PARTICIPANTS: All insured polymedicated patients. Polymedicated patients were those with a consumption of ≥16 drugs/month. MAIN OUTCOMES MEASURES: The study variables were related to age, gender and medication intake obtained from the 2008 census and records of prescriptions dispensed in pharmacies and charged to the public health system. RESULTS: There were 36 880 polymedicated patients (women: 64.2%; average age: 74.5±10.9 years). The total number of prescriptions billed in 2008 was 2 266 830 (2 272 920 total package units). The most polymedicated group (up to 40% of the total prescriptions) was patients between 75 and 84 years old. The average number of prescriptions billed monthly per patient was 32±2, with an average cost of 452.7±27.5. The total cost of those prescriptions corresponded to 2% of the drug expenditure in Catalonia. The groups N, C, A, R and M represented 71.4% of the total number of drug package units dispensed to polymedicated patients. Great variability was found between the medication profiles of men and women, and between age groups; greater discrepancies were found in paediatric patients (5-14 years) and the elderly (≥65 years). CONCLUSIONS: This study provides essential information to take steps towards rational drug use and a structured approach in the polymedicated population in primary healthcare.