1000 resultados para Identification partielle
Resumo:
Mutations in the coding sequence of SOX9 cause campomelic dysplasia (CD), a disorder of skeletal development associated with 46,XY disorders of sex development (DSDs). Translocations, deletions, and duplications within a ∼2 Mb region upstream of SOX9 can recapitulate the CD-DSD phenotype fully or partially, suggesting the existence of an unusually large cis-regulatory control region. Pierre Robin sequence (PRS) is a craniofacial disorder that is frequently an endophenotype of CD and a locus for isolated PRS at ∼1.2-1.5 Mb upstream of SOX9 has been previously reported. The craniofacial regulatory potential within this locus, and within the greater genomic domain surrounding SOX9, remains poorly defined. We report two novel deletions upstream of SOX9 in families with PRS, allowing refinement of the regions harboring candidate craniofacial regulatory elements. In parallel, ChIP-Seq for p300 binding sites in mouse craniofacial tissue led to the identification of several novel craniofacial enhancers at the SOX9 locus, which were validated in transgenic reporter mice and zebrafish. Notably, some of the functionally validated elements fall within the PRS deletions. These studies suggest that multiple noncoding elements contribute to the craniofacial regulation of SOX9 expression, and that their disruption results in PRS.
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The subdivisions of human inferior colliculus are currently based on Golgi and Nissl-stained preparations. We have investigated the distribution of calcium-binding protein immunoreactivity in the human inferior colliculus and found complementary or mutually exclusive localisations of parvalbumin versus calbindin D-28k and calretinin staining. The central nucleus of the inferior colliculus but not the surrounding regions contained parvalbumin-positive neuronal somata and fibres. Calbindin-positive neurons and fibres were concentrated in the dorsal aspect of the central nucleus and in structures surrounding it: the dorsal cortex, the lateral lemniscus, the ventrolateral nucleus, and the intercollicular region. In the dorsal cortex, labelling of calbindin and calretinin revealed four distinct layers.Thus, calcium-binding protein reactivity reveals in the human inferior colliculus distinct neuronal populations that are anatomically segregated. The different calcium-binding protein-defined subdivisions may belong to parallel auditory pathways that were previously demonstrated in non-human primates, and they may constitute a first indication of parallel processing in human subcortical auditory structures.
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Rhizoctonia-like fungi are the main mycorrhizal fungi in orchid roots. Morphological characterization and analysis of conserved sequences of genomic DNA are frequently employed in the identification and study of fungi diversity. However, phytopathogenic Rhizoctonia-like fungi have been reliably and accurately characterized and identified through the examination of the fatty acid composition. To evaluate the efficacy of fatty acid composition in characterizing and identifying Rhizoctonia-like mycorrhizal fungi in orchids, three Epulorhiza spp. mycorrhizal fungi from Epidendrum secundum, two unidentified fungi isolated from Epidendrum denticulatum, and a phytopathogenic fungus, Ceratorhiza sp. AGC, were grouped based on the profile of their fatty acids, which was assessed by the Euclidian and Mahalanobis distances and the UPGMA method. Dendrograms distinguished the phytopathogenical isolate of Ceratorhiza sp. AGC from the mycorrhizal fungi studied. The symbionts of E. secundum were grouped into two clades, one containing Epulorhiza sp.1 isolates and the other the Epulorhiza sp.2 isolate. The similarity between the symbionts of E. denticulatum and Epulorhiza spp. fungi suggests that symbionts found in E. denticulatum may be identified as Epulorhiza. These results were corroborated by the analysis of the rDNA ITS region. The dendrogram constructed based on the Mahalanobis distance differentiated the clades most clearly. Fatty acid composition analysis proved to be a useful tool for characterizing and identifying Rhizoctonia-like mycorrhizal fungi.
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Background: In haemodynamically stable patients with acute symptomatic pulmonary embolism (PE), studies have not evaluated the usefulness of combining the measurement of cardiac troponin, transthoracic echocardiogram (TTE), and lower extremity complete compression ultrasound (CCUS) testing for predicting the risk of PE-related death. Methods: The study assessed the ability of three diagnostic tests (cardiac troponin I (cTnI), echocardiogram, and CCUS) to prognosticate the primary outcome of PE-related mortality during 30 days of follow-up after a diagnosis of PE by objective testing. Results: Of 591 normotensive patients diagnosed with PE, the primary outcome occurred in 37 patients (6.3%; 95% CI 4.3% to 8.2%). Patients with right ventricular dysfunction (RVD) by TTE and concomitant deep vein thrombosis (DVT) by CCUS had a PE-related mortality of 19.6%, compared with 17.1% of patients with elevated cTnI and concomitant DVT and 15.2% of patients with elevated cTnI and RVD. The use of any two-test strategy had a higher specificity and positive predictive value compared with the use of any test by itself. A combined three-test strategy did not further improve prognostication. For a subgroup analysis of high-risk patients, according to the pulmonary embolism severity index (classes IV and V), positive predictive values of the two-test strategies for PE-related mortality were 25.0%, 24.4% and 20.7%, respectively. Conclusions: In haemodynamically stable patients with acute symptomatic PE, a combination of echocardiography (or troponin testing) and CCUS improved prognostication compared with the use of any test by itself for the identification of those at high risk of PE-related death.
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Caprine and ovine IgA were identified by cross-reaction with anti-human and anti-bovine IgA sera in colostrum, mature milk, saliva, urine and serum. Secretory component (SC) was shown in the free form and associated with polymeric serum IgA in secretions. Mean molecular weights were determined for the IgA and the free secretory components. The high IgA content of saliva suggested that it was a major secretory immunoglobulin in these species. Traces of secretory IgA were also found in normal sera but most of the serum IgA had no secretory determinant. Secretory IgA, serum IgA and free secretory component were purified. Levels of the sheep and goat immunoglobulins were measured in various fluids.
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Selostus: Kolmen uuden mesimarjalajikkeen kuvaukset ja lajikekuvausohjeet mesimarjalle ja jalomaaraimelle
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ObjectiveCandidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.Research Design and MethodsBy integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twenty-one tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS).Results273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations.ConclusionsUsing a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS.
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Over the past few decades, Fourier transform infrared (FTIR) spectroscopy coupled to microscopy has been recognized as an emerging and potentially powerful tool in cancer research and diagnosis. For this purpose, histological analyses performed by pathologists are mostly carried out on biopsied tissue that undergoes the formalin-fixation and paraffin-embedding (FFPE) procedure. This processing method ensures an optimal and permanent preservation of the samples, making FFPE-archived tissue an extremely valuable source for retrospective studies. Nevertheless, as highlighted by previous studies, this fixation procedure significantly changes the principal constituents of cells, resulting in important effects on their infrared (IR) spectrum. Despite the chemical and spectral influence of FFPE processing, some studies demonstrate that FTIR imaging allows precise identification of the different cell types present in biopsied tissue, indicating that the FFPE process preserves spectral differences between distinct cell types. In this study, we investigated whether this is also the case for closely related cell lines. We analyzed spectra from 8 cancerous epithelial cell lines: 4 breast cancer cell lines and 4 melanoma cell lines. For each cell line, we harvested cells at subconfluence and divided them into two sets. We first tested the "original" capability of FTIR imaging to identify these closely related cell lines on cells just dried on BaF2 slides. We then repeated the test after submitting the cells to the FFPE procedure. Our results show that the IR spectra of FFPE processed cancerous cell lines undergo small but significant changes due to the treatment. The spectral modifications were interpreted as a potential decrease in the phospholipid content and protein denaturation, in line with the scientific literature on the topic. Nevertheless, unsupervised analyses showed that spectral proximities and distances between closely related cell lines were mostly, but not entirely, conserved after FFPE processing. Finally, PLS-DA statistical analyses highlighted that closely related cell lines are still successfully identified and efficiently distinguished by FTIR spectroscopy after FFPE treatment. This last result paves the way towards identification and characterization of cellular subtypes on FFPE tissue sections by FTIR imaging, indicating that this analysis technique could become a potential useful tool in cancer research.
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Ces dernières années, de nombreuses recherches ont mis en évidence les effets toxiques des micropolluants organiques pour les espèces de nos lacs et rivières. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, alors que les organismes sont exposés tous les jours à des milliers de substances en mélange. Or les effets de ces cocktails ne sont pas négligeables. Cette thèse de doctorat s'est ainsi intéressée aux modèles permettant de prédire le risque environnemental de ces cocktails pour le milieu aquatique. Le principal objectif a été d'évaluer le risque écologique des mélanges de substances chimiques mesurées dans le Léman, mais aussi d'apporter un regard critique sur les méthodologies utilisées afin de proposer certaines adaptations pour une meilleure estimation du risque. Dans la première partie de ce travail, le risque des mélanges de pesticides et médicaments pour le Rhône et pour le Léman a été établi en utilisant des approches envisagées notamment dans la législation européenne. Il s'agit d'approches de « screening », c'est-à-dire permettant une évaluation générale du risque des mélanges. Une telle approche permet de mettre en évidence les substances les plus problématiques, c'est-à-dire contribuant le plus à la toxicité du mélange. Dans notre cas, il s'agit essentiellement de 4 pesticides. L'étude met également en évidence que toutes les substances, même en trace infime, contribuent à l'effet du mélange. Cette constatation a des implications en terme de gestion de l'environnement. En effet, ceci implique qu'il faut réduire toutes les sources de polluants, et pas seulement les plus problématiques. Mais l'approche proposée présente également un biais important au niveau conceptuel, ce qui rend son utilisation discutable, en dehors d'un screening, et nécessiterait une adaptation au niveau des facteurs de sécurité employés. Dans une deuxième partie, l'étude s'est portée sur l'utilisation des modèles de mélanges dans le calcul de risque environnemental. En effet, les modèles de mélanges ont été développés et validés espèce par espèce, et non pour une évaluation sur l'écosystème en entier. Leur utilisation devrait donc passer par un calcul par espèce, ce qui est rarement fait dû au manque de données écotoxicologiques à disposition. Le but a été donc de comparer, avec des valeurs générées aléatoirement, le calcul de risque effectué selon une méthode rigoureuse, espèce par espèce, avec celui effectué classiquement où les modèles sont appliqués sur l'ensemble de la communauté sans tenir compte des variations inter-espèces. Les résultats sont dans la majorité des cas similaires, ce qui valide l'approche utilisée traditionnellement. En revanche, ce travail a permis de déterminer certains cas où l'application classique peut conduire à une sous- ou sur-estimation du risque. Enfin, une dernière partie de cette thèse s'est intéressée à l'influence que les cocktails de micropolluants ont pu avoir sur les communautés in situ. Pour ce faire, une approche en deux temps a été adoptée. Tout d'abord la toxicité de quatorze herbicides détectés dans le Léman a été déterminée. Sur la période étudiée, de 2004 à 2009, cette toxicité due aux herbicides a diminué, passant de 4% d'espèces affectées à moins de 1%. Ensuite, la question était de savoir si cette diminution de toxicité avait un impact sur le développement de certaines espèces au sein de la communauté des algues. Pour ce faire, l'utilisation statistique a permis d'isoler d'autres facteurs pouvant avoir une influence sur la flore, comme la température de l'eau ou la présence de phosphates, et ainsi de constater quelles espèces se sont révélées avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps. Fait intéressant, une partie d'entre-elles avait déjà montré des comportements similaires dans des études en mésocosmes. En conclusion, ce travail montre qu'il existe des modèles robustes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques, et qu'ils peuvent être utilisés pour expliquer le rôle des substances dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application. - Depuis plusieurs années, les risques que posent les micropolluants organiques pour le milieu aquatique préoccupent grandement les scientifiques ainsi que notre société. En effet, de nombreuses recherches ont mis en évidence les effets toxiques que peuvent avoir ces substances chimiques sur les espèces de nos lacs et rivières, quand elles se retrouvent exposées à des concentrations aiguës ou chroniques. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, c'est à dire considérées séparément. Actuellement, il en est de même dans les procédures de régulation européennes, concernant la partie évaluation du risque pour l'environnement d'une substance. Or, les organismes sont exposés tous les jours à des milliers de substances en mélange, et les effets de ces "cocktails" ne sont pas négligeables. L'évaluation du risque écologique que pose ces mélanges de substances doit donc être abordé par de la manière la plus appropriée et la plus fiable possible. Dans la première partie de cette thèse, nous nous sommes intéressés aux méthodes actuellement envisagées à être intégrées dans les législations européennes pour l'évaluation du risque des mélanges pour le milieu aquatique. Ces méthodes sont basées sur le modèle d'addition des concentrations, avec l'utilisation des valeurs de concentrations des substances estimées sans effet dans le milieu (PNEC), ou à partir des valeurs des concentrations d'effet (CE50) sur certaines espèces d'un niveau trophique avec la prise en compte de facteurs de sécurité. Nous avons appliqué ces méthodes à deux cas spécifiques, le lac Léman et le Rhône situés en Suisse, et discuté les résultats de ces applications. Ces premières étapes d'évaluation ont montré que le risque des mélanges pour ces cas d'étude atteint rapidement une valeur au dessus d'un seuil critique. Cette valeur atteinte est généralement due à deux ou trois substances principales. Les procédures proposées permettent donc d'identifier les substances les plus problématiques pour lesquelles des mesures de gestion, telles que la réduction de leur entrée dans le milieu aquatique, devraient être envisagées. Cependant, nous avons également constaté que le niveau de risque associé à ces mélanges de substances n'est pas négligeable, même sans tenir compte de ces substances principales. En effet, l'accumulation des substances, même en traces infimes, atteint un seuil critique, ce qui devient plus difficile en terme de gestion du risque. En outre, nous avons souligné un manque de fiabilité dans ces procédures, qui peuvent conduire à des résultats contradictoires en terme de risque. Ceci est lié à l'incompatibilité des facteurs de sécurité utilisés dans les différentes méthodes. Dans la deuxième partie de la thèse, nous avons étudié la fiabilité de méthodes plus avancées dans la prédiction de l'effet des mélanges pour les communautés évoluant dans le système aquatique. Ces méthodes reposent sur le modèle d'addition des concentrations (CA) ou d'addition des réponses (RA) appliqués sur les courbes de distribution de la sensibilité des espèces (SSD) aux substances. En effet, les modèles de mélanges ont été développés et validés pour être appliqués espèce par espèce, et non pas sur plusieurs espèces agrégées simultanément dans les courbes SSD. Nous avons ainsi proposé une procédure plus rigoureuse, pour l'évaluation du risque d'un mélange, qui serait d'appliquer d'abord les modèles CA ou RA à chaque espèce séparément, et, dans une deuxième étape, combiner les résultats afin d'établir une courbe SSD du mélange. Malheureusement, cette méthode n'est pas applicable dans la plupart des cas, car elle nécessite trop de données généralement indisponibles. Par conséquent, nous avons comparé, avec des valeurs générées aléatoirement, le calcul de risque effectué selon cette méthode plus rigoureuse, avec celle effectuée traditionnellement, afin de caractériser la robustesse de cette approche qui consiste à appliquer les modèles de mélange sur les courbes SSD. Nos résultats ont montré que l'utilisation de CA directement sur les SSDs peut conduire à une sous-estimation de la concentration du mélange affectant 5 % ou 50% des espèces, en particulier lorsque les substances présentent un grand écart- type dans leur distribution de la sensibilité des espèces. L'application du modèle RA peut quant à lui conduire à une sur- ou sous-estimations, principalement en fonction de la pente des courbes dose- réponse de chaque espèce composant les SSDs. La sous-estimation avec RA devient potentiellement importante lorsque le rapport entre la EC50 et la EC10 de la courbe dose-réponse des espèces est plus petit que 100. Toutefois, la plupart des substances, selon des cas réels, présentent des données d' écotoxicité qui font que le risque du mélange calculé par la méthode des modèles appliqués directement sur les SSDs reste cohérent et surestimerait plutôt légèrement le risque. Ces résultats valident ainsi l'approche utilisée traditionnellement. Néanmoins, il faut garder à l'esprit cette source d'erreur lorsqu'on procède à une évaluation du risque d'un mélange avec cette méthode traditionnelle, en particulier quand les SSD présentent une distribution des données en dehors des limites déterminées dans cette étude. Enfin, dans la dernière partie de cette thèse, nous avons confronté des prédictions de l'effet de mélange avec des changements biologiques observés dans l'environnement. Dans cette étude, nous avons utilisé des données venant d'un suivi à long terme d'un grand lac européen, le lac Léman, ce qui offrait la possibilité d'évaluer dans quelle mesure la prédiction de la toxicité des mélanges d'herbicide expliquait les changements dans la composition de la communauté phytoplanctonique. Ceci à côté d'autres paramètres classiques de limnologie tels que les nutriments. Pour atteindre cet objectif, nous avons déterminé la toxicité des mélanges sur plusieurs années de 14 herbicides régulièrement détectés dans le lac, en utilisant les modèles CA et RA avec les courbes de distribution de la sensibilité des espèces. Un gradient temporel de toxicité décroissant a pu être constaté de 2004 à 2009. Une analyse de redondance et de redondance partielle, a montré que ce gradient explique une partie significative de la variation de la composition de la communauté phytoplanctonique, même après avoir enlevé l'effet de toutes les autres co-variables. De plus, certaines espèces révélées pour avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps, ont montré des comportements similaires dans des études en mésocosmes. On peut en conclure que la toxicité du mélange herbicide est l'un des paramètres clés pour expliquer les changements de phytoplancton dans le lac Léman. En conclusion, il existe diverses méthodes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques et celui-ci peut jouer un rôle dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application, avant d'utiliser leurs résultats pour la gestion des risques environnementaux. - For several years now, the scientists as well as the society is concerned by the aquatic risk organic micropollutants may pose. Indeed, several researches have shown the toxic effects these substances may induce on organisms living in our lakes or rivers, especially when they are exposed to acute or chronic concentrations. However, most of the studies focused on the toxicity of single compounds, i.e. considered individually. The same also goes in the current European regulations concerning the risk assessment procedures for the environment of these substances. But aquatic organisms are typically exposed every day simultaneously to thousands of organic compounds. The toxic effects resulting of these "cocktails" cannot be neglected. The ecological risk assessment of mixtures of such compounds has therefore to be addressed by scientists in the most reliable and appropriate way. In the first part of this thesis, the procedures currently envisioned for the aquatic mixture risk assessment in European legislations are described. These methodologies are based on the mixture model of concentration addition and the use of the predicted no effect concentrations (PNEC) or effect concentrations (EC50) with assessment factors. These principal approaches were applied to two specific case studies, Lake Geneva and the River Rhône in Switzerland, including a discussion of the outcomes of such applications. These first level assessments showed that the mixture risks for these studied cases exceeded rapidly the critical value. This exceeding is generally due to two or three main substances. The proposed procedures allow therefore the identification of the most problematic substances for which management measures, such as a reduction of the entrance to the aquatic environment, should be envisioned. However, it was also showed that the risk levels associated with mixtures of compounds are not negligible, even without considering these main substances. Indeed, it is the sum of the substances that is problematic, which is more challenging in term of risk management. Moreover, a lack of reliability in the procedures was highlighted, which can lead to contradictory results in terms of risk. This result is linked to the inconsistency in the assessment factors applied in the different methods. In the second part of the thesis, the reliability of the more advanced procedures to predict the mixture effect to communities in the aquatic system were investigated. These established methodologies combine the model of concentration addition (CA) or response addition (RA) with species sensitivity distribution curves (SSD). Indeed, the mixture effect predictions were shown to be consistent only when the mixture models are applied on a single species, and not on several species simultaneously aggregated to SSDs. Hence, A more stringent procedure for mixture risk assessment is proposed, that would be to apply first the CA or RA models to each species separately and, in a second step, to combine the results to build an SSD for a mixture. Unfortunately, this methodology is not applicable in most cases, because it requires large data sets usually not available. Therefore, the differences between the two methodologies were studied with datasets created artificially to characterize the robustness of the traditional approach applying models on species sensitivity distribution. The results showed that the use of CA on SSD directly might lead to underestimations of the mixture concentration affecting 5% or 50% of species, especially when substances present a large standard deviation of the distribution from the sensitivity of the species. The application of RA can lead to over- or underestimates, depending mainly on the slope of the dose-response curves of the individual species. The potential underestimation with RA becomes important when the ratio between the EC50 and the EC10 for the dose-response curve of the species composing the SSD are smaller than 100. However, considering common real cases of ecotoxicity data for substances, the mixture risk calculated by the methodology applying mixture models directly on SSDs remains consistent and would rather slightly overestimate the risk. These results can be used as a theoretical validation of the currently applied methodology. Nevertheless, when assessing the risk of mixtures, one has to keep in mind this source of error with this classical methodology, especially when SSDs present a distribution of the data outside the range determined in this study Finally, in the last part of this thesis, we confronted the mixture effect predictions with biological changes observed in the environment. In this study, long-term monitoring of a European great lake, Lake Geneva, provides the opportunity to assess to what extent the predicted toxicity of herbicide mixtures explains the changes in the composition of the phytoplankton community next to other classical limnology parameters such as nutrients. To reach this goal, the gradient of the mixture toxicity of 14 herbicides regularly detected in the lake was calculated, using concentration addition and response addition models. A decreasing temporal gradient of toxicity was observed from 2004 to 2009. Redundancy analysis and partial redundancy analysis showed that this gradient explains a significant portion of the variation in phytoplankton community composition, even when having removed the effect of all other co-variables. Moreover, some species that were revealed to be influenced positively or negatively, by the decrease of toxicity in the lake over time, showed similar behaviors in mesocosms studies. It could be concluded that the herbicide mixture toxicity is one of the key parameters to explain phytoplankton changes in Lake Geneva. To conclude, different methods exist to predict the risk of mixture in the ecosystems. But their reliability varies depending on the underlying hypotheses. One should therefore carefully consider these hypotheses, as well as the limits of the approaches, before using the results for environmental risk management
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The autosomal recessive forms of limb-girdle muscular dystrophies are encoded by at least five distinct genes. The work performed towards the identification of two of these is summarized in this report. This success illustrates the growing importance of genetics in modern nosology.
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The use of synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) has emerged recently as an alternative approach for the identification of peptides recognized by T lymphocytes. The choice of both the PS-SCL used for screening experiments and the method used for data analysis are crucial for implementing this approach. With this aim, we tested the recognition of different PS-SCL by a tyrosinase 368-376-specific CTL clone and analyzed the data obtained with a recently developed biometric data analysis based on a model of independent and additive contribution of individual amino acids to peptide antigen recognition. Mixtures defined with amino acids present at the corresponding positions in the native sequence were among the most active for all of the libraries. Somewhat surprisingly, a higher number of native amino acids were identifiable by using amidated COOH-terminal rather than free COOH-terminal PS-SCL. Also, our data clearly indicate that when using PS-SCL longer than optimal, frame shifts occur frequently and should be taken into account. Biometric analysis of the data obtained with the amidated COOH-terminal nonapeptide library allowed the identification of the native ligand as the sequence with the highest score in a public human protein database. However, the adequacy of the PS-SCL data for the identification for the peptide ligand varied depending on the PS-SCL used. Altogether these results provide insight into the potential of PS-SCL for the identification of CTL-defined tumor-derived antigenic sequences and may significantly implement our ability to interpret the results of these analyses.
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The equilibrium of membrane fusion and fission influences the volume and copy number of organelles. Fusion of yeast vacuoles has been well characterized but their fission and the mechanisms determining vacuole size and abundance remain poorly understood. We therefore attempted to systematically characterize factors necessary for vacuole fission. Here, we present results of an in vivo screening for deficiencies in vacuolar fragmentation activity of an ordered collection deletion mutants, representing 4881 non-essential genes of the yeast Saccharomyces cerevisiae. The screen identified 133 mutants with strong defects in vacuole fragmentation. These comprise numerous known fragmentation factors, such as the Fab1p complex, Tor1p, Sit4p and the V-ATPase, thus validating the approach. The screen identified many novel factors promoting vacuole fragmentation. Among those are 22 open reading frames of unknown function and three conspicuous clusters of proteins with known function. The clusters concern the ESCRT machinery, adaptins, and lipases, which influence the production of diacylglycerol and phosphatidic acid. A common feature of these factors of known function is their capacity to change membrane curvature, suggesting that they might promote vacuole fragmentation via this property.
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PURPOSE: To objectively characterize different heart tissues from functional and viability images provided by composite-strain-encoding (C-SENC) MRI. MATERIALS AND METHODS: C-SENC is a new MRI technique for simultaneously acquiring cardiac functional and viability images. In this work, an unsupervised multi-stage fuzzy clustering method is proposed to identify different heart tissues in the C-SENC images. The method is based on sequential application of the fuzzy c-means (FCM) and iterative self-organizing data (ISODATA) clustering algorithms. The proposed method is tested on simulated heart images and on images from nine patients with and without myocardial infarction (MI). The resulting clustered images are compared with MRI delayed-enhancement (DE) viability images for determining MI. Also, Bland-Altman analysis is conducted between the two methods. RESULTS: Normal myocardium, infarcted myocardium, and blood are correctly identified using the proposed method. The clustered images correctly identified 90 +/- 4% of the pixels defined as infarct in the DE images. In addition, 89 +/- 5% of the pixels defined as infarct in the clustered images were also defined as infarct in DE images. The Bland-Altman results show no bias between the two methods in identifying MI. CONCLUSION: The proposed technique allows for objectively identifying divergent heart tissues, which would be potentially important for clinical decision-making in patients with MI.
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ABSTRACT Trichoderma species are non-pathogenic microorganisms that protect against fungal diseases and contribute to increased crop yields. However, not all Trichoderma species have the same effects on crop or a pathogen, whereby the characterization and identification of strains at the species level is the first step in the use of a microorganism. The aim of this study was the identification – at species level – of five strains of Trichoderma isolated from soil samples obtained from garlic and onion fields located in Costa Rica, through the analysis of the ITS1, 5.8S, and ITS2 ribosomal RNA regions; as well as the determination of their individual antagonistic ability over S. cepivorum Berkeley. In order to distinguish the strains, the amplified products were analyzed using MEGA v6.0 software, calculating the genetic distances through the Tamura-Nei model and building the phylogenetic tree using the Maximum Likelihood method. We established that the evaluated strains belonged to the species T. harzianum and T. asperellum; however it was not possible to identify one of the analyzed strains based on the species criterion. To evaluate their antagonistic ability, the dual culture technique, Bell’s scale, and the percentage inhibition of radial growth (PIRG) were used, evidencing that one of the T. asperellum isolates presented the best yields under standard, solid fermentation conditions.
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Aim The jaguar, Panthera onca, is a species of global conservation concern. In Mexico, the northernmost part of its distribution range, its conservation status, is particularly critical, while its potential and actual distribution is poorly known. We propose an ensemble model (EM) of the potential distribution for the jaguar in Mexico and identify the priority areas for conservation.Location Mexico.Methods We generated our EM based on three presence-only methods (Ecological Niche Factor Analysis, Mahalanobis distance, Maxent) and considering environmental, biological and anthropogenic factors. We used this model to evaluate the efficacy of the existing Mexican protected areas (PAs), to evaluate the adequacy of the jaguar conservation units (JCUs) and to propose new areas that should be considered for conservation and management of the species in Mexico.Results Our results outline that 16% of Mexico (c. 312,000 km2) can be considered as suitable for the presence of the jaguar. Furthermore, 13% of the suitable areas are included in existing PAs and 14% are included in JCUs (Sanderson et al., 2002).Main conclusions Clearly much more should be carried out to establish a proactive conservation strategy. Based on our results, we propose here new jaguar conservation and management areas that are important for a nationwide conservation blueprint.