207 resultados para common bile duct calcul


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Astrocyte reactivity is a hallmark of neurodegenerative diseases (ND), but its effects on disease outcomes remain highly debated. Elucidation of the signaling cascades inducing reactivity in astrocytes during ND would help characterize the function of these cells and identify novel molecular targets to modulate disease progression. The Janus kinase/signal transducer and activator of transcription 3 (JAK/STAT3) pathway is associated with reactive astrocytes in models of acute injury, but it is unknown whether this pathway is directly responsible for astrocyte reactivity in progressive pathological conditions such as ND. In this study, we examined whether the JAK/STAT3 pathway promotes astrocyte reactivity in several animal models of ND. The JAK/STAT3 pathway was activated in reactive astrocytes in two transgenic mouse models of Alzheimer's disease and in a mouse and a nonhuman primate lentiviral vector-based model of Huntington's disease (HD). To determine whether this cascade was instrumental for astrocyte reactivity, we used a lentiviral vector that specifically targets astrocytes in vivo to overexpress the endogenous inhibitor of the JAK/STAT3 pathway [suppressor of cytokine signaling 3 (SOCS3)]. SOCS3 significantly inhibited this pathway in astrocytes, prevented astrocyte reactivity, and decreased microglial activation in models of both diseases. Inhibition of the JAK/STAT3 pathway within reactive astrocytes also increased the number of huntingtin aggregates, a neuropathological hallmark of HD, but did not influence neuronal death. Our data demonstrate that the JAK/STAT3 pathway is a common mediator of astrocyte reactivity that is highly conserved between disease states, species, and brain regions. This universal signaling cascade represents a potent target to study the role of reactive astrocytes in ND.

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Sex-chromosome differentiation was recently shown to vary among common frog populations in Fennoscandia, suggesting a trend of increased differentiation with latitude. By rearing families from two contrasted populations (respectively, from northern and southern Sweden), we show this disparity to stem from differences in sex-determination mechanisms rather than in XY-recombination patterns. Offspring from the northern population display equal sex ratios at metamorphosis, with phenotypic sexes that correlate strongly with paternal LG2 haplotypes (the sex chromosome); accordingly, Y haplotypes are markedly differentiated, with male-specific alleles and depressed diversity testifying to their smaller effective population size. In the southern population, by contrast, a majority of juveniles present ovaries at metamorphosis; only later in development do sex ratios return to equilibrium. Even at these later stages, phenotypic sexes correlate only mildly with paternal LG2 haplotypes; accordingly, there are no recognizable Y haplotypes. These distinct patterns of gonadal development fit the concept of 'sex races' proposed in the 1930s, with our two populations assigned to the 'differentiated' and 'semi-differentiated' races, respectively. Our results support the suggestion that 'sex races' differ in the genetic versus epigenetic components of sex determination. Analysing populations from the 'undifferentiated race' with high-density genetic maps should help to further test this hypothesis.

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The case of a 41-year-old alcoholic patient who presented with massive upper gastrointestinal bleeding is reported. The diagnosis was established rapidly by endoscopy which revealed bleeding through the papilla of Vater. Selective angiography of the superior mesenteric artery opacified the pancreatic duct as well as the duodenum. CT scan showed signs of chronic pancreatitis. Because of the recurrence of bleeding and shock, an urgent operation was necessary and a Whipple procedure was performed. Recovery was complete. The clinical presentation, the etiology, the diagnostic modalities and the treatment of this particular condition are discussed. Usually, hemorrhage through the pancreatic duct presents as repeated episodes of upper gastrointestinal bleeding with no source found at endoscopy. The presence of chronic pancreatitis or of epigastric pain during bleeding should suggest the diagnosis. Upper gastrointestinal endoscopy and angiography are the principal diagnostic tools. Definitive treatment requires surgery, and resection in most of the cases.

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In this commentary, we argue that the term 'prediction' is overly used when in fact, referring to foundational writings of de Finetti, the correspondent term should be inference. In particular, we intend (i) to summarize and clarify relevant subject matter on prediction from established statistical theory, and (ii) point out the logic of this understanding with respect practical uses of the term prediction. Written from an interdisciplinary perspective, associating statistics and forensic science as an example, this discussion also connects to related fields such as medical diagnosis and other areas of application where reasoning based on scientific results is practiced in societal relevant contexts. This includes forensic psychology that uses prediction as part of its vocabulary when dealing with matters that arise in the course of legal proceedings.

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Over the past two decades, an increasing amount of phylogeographic work has substantially improved our understanding of African biogeography, in particular the role played by Pleistocene pluvial-drought cycles on terrestrial vertebrates. However, still little is known on the evolutionary history of semi-aquatic animals, which faced tremendous challenges imposed by unpredictable availability of water resources. In this study, we investigate the Late Pleistocene history of the common hippopotamus (Hippopotamus amphibius), using mitochondrial and nuclear DNA sequence variation and range-wide sampling. We documented a global demographic and spatial expansion approximately 0.1-0.3 Myr ago, most likely associated with an episode of massive drainage overflow. These events presumably enabled a historical continent-wide gene flow among hippopotamus populations, and hence, no clear continental-scale genetic structuring remains. Nevertheless, present-day hippopotamus populations are genetically disconnected, probably as a result of the mid-Holocene aridification and contemporary anthropogenic pressures. This unique pattern contrasts with the biogeographic paradigms established for savannah-adapted ungulate mammals and should be further investigated in other water-associated taxa. Our study has important consequences for the conservation of the hippo, an emblematic but threatened species that requires specific protection to curtail its long-term decline.

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Objectifs La chirurgie pancréatique reste associée à une morbidité postopératoire importante. Les efforts sont concentrés la plupart du temps sur la diminution de cette morbidité, mais la détection précoce de patients à risque de complications pourrait être une autre stratégie valable. Un score simple de prédiction des complications après duodénopancréatectomie céphalique a récemment été publié par Braga et al. La présente étude a pour but de valider ce score et de discuter de ses possibles implications cliniques. Méthodes De 2000 à 2015, 245 patients ont bénéficié d'une duodénopancréatectomie céphalique dans notre service. Les complications postopératoires ont été recensées selon la classification de Dindo et Clavien. Le score de Braga se base sur quatre paramètres : le score ASA (American Society of Anesthesiologists), la texture du pancréas, le diamètre du canal de Wirsung (canal pancréatique principal) et les pertes sanguines intra-opératoires. Un score de risque global de 0 à 15 peut être calculé pour chaque patient. La puissance de discrimination du score a été calculée en utilisant une courbe ROC (receiver operating characteristic). Résultats Des complications majeures sont apparues chez 31% des patients, alors que 17% des patients ont eu des complications majeures dans l'article de Braga. La texture du pancréas et les pertes sanguines étaient statistiquement significativement corrélées à une morbidité accrue. Les aires sous la courbe étaient respectivement de 0.95 et 0.99 pour les scores classés en quatre catégories de risques (de 0 à 3, 4 à 7, 8 à 11 et 12 à 15) et pour les scores individuels (de 0 à 15). Conclusions Le score de Braga permet donc une bonne discrimination entre les complications mineures et majeures. Notre étude de validation suggère que ce score peut être utilisé comme un outil pronostique de complications majeures après duodénopancréatectomie céphalique. Les implications cliniques, c'est-à-dire si les stratégies de prise en charge postopératoire doivent être adaptées en fonction du risque individuel du patient, restent cependant à élucider. -- Objectives Pancreatic surgery remains associated with important morbidity. Efforts are most commonly concentrated on decreasing postoperative morbidity, but early detection of patients at risk could be another valuable strategy. A simple prognostic score has recently been published. This study aimed to validate this score and discuss possible clinical implications. Methods From 2000 to 2012, 245 patients underwent pancreaticoduodenectomy. Complications were graded according to the Dindo-Clavien classification. The Braga score is based on American Society of Anesthesiologists score, pancreatic texture, Wirsung duct diameter, and blood loss. An overall risk score (from 0 to 15) can be calculated for each patient. Score discriminant power was calculated using a receiver operating characteristic curve. Results Major complications occurred in 31% of patients compared to 17% in Braga's data. Pancreatic texture and blood loss were independently statistically significant for increased morbidity. The areas under curve were 0.95 and 0.99 for 4-risk categories and for individual scores, respectively. Conclusions The Braga score discriminates well between minor and major complications. Our validation suggests that it can be used as prognostic tool for major complications after pancreaticoduodenectomy. The clinical implications, i.e., whether postoperative treatment strategies should be adapted according to the patient's individual risk, remain to be elucidated.

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BACKGROUND AND AIMS: Formerly obese patients having undergone Roux-en-Y gastric bypass (RYGB) display both an accelerated digestion and absorption of carbohydrate and an increased plasma glucose clearance rate after meal ingestion. How RYGB effects postprandial kinetics of dietary lipids has yet not been investigated. METHODS: Plasma triglyceride (TG), apoB48, total apoB, bile acids (BA), fibroblast growth factor 19 (FGF19), and cholecystokinin (CCK) were measured in post-absorptive conditions and over 4-h following the ingestion of a mixed test meal in a cross-sectional, pilot study involving 11 formerly obese female patients 33.8 ± 16.4 months after RYGB surgery and in 11 weight- and age-matched female control participants. RESULTS: Compared to controls, RYGB patients had faster (254 ± 14 vs. 327 ± 7 min, p < 0.05) and lower (0.14 ± 0.04 vs. 0.35 ± 0.07 mM, p < 0.05) peak TG responses, but their peak apoB48 responses tended to be higher (2692 ± 336 vs. 1841 ± 228 ng/ml, p = 0.09). Their postprandial total BA concentrations were significantly increased and peaked earlier after meal ingestion than in controls. Their FGF19 and CCK concentrations also peaked earlier and to a higher value. CONCLUSIONS: The early postprandial apoB48 and BA responses indicate that RYGB accelerated the rate of dietary lipid absorption. The lower postprandial peak TG strongly suggests that the RYGB simultaneously increased the clearance of TG-rich lipoproteins. CLINICAL TRIAL REGISTRATION: NCT01891591.

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OBJECTIVES: The aims of the study were to use cone beam computed tomography (CBCT) images of nasopalatine duct cysts (NPDC) and to calculate the diameter, surface area, and 3D-volume using a custom-made software program. Furthermore, any associations of dimensions of NPDC with age, gender, presence/absence of maxillary incisors/canines (MI/MC), endodontic treatment of MI/MC, presenting symptoms, and postoperative complications were evaluated. MATERIAL AND METHODS: The study comprised 40 patients with a histopathologically confirmed NPDC. On preoperative CBCT scans, curves delineating the cystic borders were drawn in all planes and the widest diameter (in millimeter), surface area (in square millimeter), and volume (in cubic millimeter) were calculated. RESULTS: The overall mean cyst diameter was 15 mm (range 7-47 mm), the mean cyst surface area 566 mm(2) (84-4,516 mm(2)), and the mean cyst volume 1,735 mm(3) (65-25,350 mm(3)). For 22 randomly allocated cases, a second measurement resulted in a mean absolute aberration of ±4.2 % for the volume, ±2.8 % for the surface, and ±4.9 % for the diameter. A statistically significant association was found for the CBCT determined cyst measurements and the need for preoperative endodontic treatment to MI/MC and for postoperative complications. CONCLUSION: In the hands of a single experienced operator, the novel software exhibited high repeatability for measurements of cyst dimensions. Further studies are needed to assess the application of this tool for dimensional analysis of different jaw cysts and lesions including treatment planning. CLINICAL RELEVANCE: Accurate radiographic information of the bone volume lost (osteolysis) due to expansion of a cystic lesion in three dimensions could help in personalized treatment planning.

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Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.

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OBJECTIVE: The natural course of chronic hepatitis C varies widely. To improve the profiling of patients at risk of developing advanced liver disease, we assessed the relative contribution of factors for liver fibrosis progression in hepatitis C. DESIGN: We analysed 1461 patients with chronic hepatitis C with an estimated date of infection and at least one liver biopsy. Risk factors for accelerated fibrosis progression rate (FPR), defined as ≥0.13 Metavir fibrosis units per year, were identified by logistic regression. Examined factors included age at infection, sex, route of infection, HCV genotype, body mass index (BMI), significant alcohol drinking (≥20 g/day for ≥5 years), HIV coinfection and diabetes. In a subgroup of 575 patients, we assessed the impact of single nucleotide polymorphisms previously associated with fibrosis progression in genome-wide association studies. Results were expressed as attributable fraction (AF) of risk for accelerated FPR. RESULTS: Age at infection (AF 28.7%), sex (AF 8.2%), route of infection (AF 16.5%) and HCV genotype (AF 7.9%) contributed to accelerated FPR in the Swiss Hepatitis C Cohort Study, whereas significant alcohol drinking, anti-HIV, diabetes and BMI did not. In genotyped patients, variants at rs9380516 (TULP1), rs738409 (PNPLA3), rs4374383 (MERTK) (AF 19.2%) and rs910049 (major histocompatibility complex region) significantly added to the risk of accelerated FPR. Results were replicated in three additional independent cohorts, and a meta-analysis confirmed the role of age at infection, sex, route of infection, HCV genotype, rs738409, rs4374383 and rs910049 in accelerating FPR. CONCLUSIONS: Most factors accelerating liver fibrosis progression in chronic hepatitis C are unmodifiable.