995 resultados para Hepatic Elimination Models
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Background and aim: Wilson disease (WD) is an inherited disorder ofhepatic copper excretion leading to toxic accumulation of copper in theliver as well as the brain, cornea, and other organs. The defect is due tomutations of the copper-transporting ATPase ATP7B. Here, we describethe adult cases of hepatic WD diagnosed at the CHUV between 2005and 2010.Methods: Clinical manifestions, results of diagnostic tests, and follow-upof adult patients with hepatic WD were recorded systematically.Results: Seven new adult cases of hepatic WD were diagnosed in ourcenter between 2005 and 2010. Three were women and 4 men, with amedian a ge at d iagnosis o f 24 (range, 1 8-56) years. Three patientspresented with acute liver failure (ALF), three with persistently elevatedliver function tests, and one with a dvanced cirrhosis. None hadneurological manifestations. Only one patient, presenting with ALF, had aKayser-Fleischer corneal ring. Median ceruloplasmin levels at diagnosiswere 0.13 (range, <0.03-0.30) g/l, median 24 h urinary copper excretion6.3 (range, 0.4-62.0) μmol/24 h, and median hepatic copperconcentration 591 (range, 284-1049) μg/g. At least one mutation in theATP7B g ene was i dentified in a ll patients. Allelic frequency of t hecommon H1069Q mutation was 14%. Two patients presenting with ALFand the one with advanced cirrhosis underwent successful l ivertransplantation. One patient with ALF recovered under chelator therapy.D-penicillamine was used as first-line chelator treatment, with a switch totrientine due to adverse effects in 2 out of 4 patients u nder l ong-termtreatment.Conclusions: The clinical presentation of WD and the performance ofdiagnostic tests are variable. A high index of suspicion i n clinicallycompatible situations i s key, with a combination of tests allowing thediagnosis of WD.
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Inflammatory processes described in Parkinson’s disease (PD) and its animal models appear to be important in the progression of the pathogenesis, or even a triggering factor. Here we review that peripheral inflammation enhances the degeneration of the nigrostriatal dopaminergic system induced by different insults; different peripheral inflammations have been used, such as IL-1β and the ulcerative colitis model, as well as insults to the dopaminergic system such as 6-hydroxydopamine or lipopolysaccharide. In all cases, an increased loss of dopaminergic neurons was described; inflammation in the substantia nigra increased, displaying a great activation of microglia along with an increase in the production of cytokines such as IL-1β and TNF-α. Increased permeability or disruption of the BBB, with overexpression of the ICAM-1 adhesion molecule and infiltration of circulating monocytes into the substantia nigra, is also involved, since the depletion of circulating monocytes prevents the effects of peripheral inflammation. Data are reviewed in relation to epidemiological studies of PD.
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Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants
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Follow-up of the household contacts (HHC) of leprosy patients is still the best strategy for early detection of leprosy. HHC from a post-elimination region of Colombia studied in 2001-2002 were re-contacted in 2007. They were tested at both times by clinical examination, bacillary index (BI), PCR from a slit skin smear (SSS) and anti PGL-1 IgM titres. Thirty-two of 61 HHC (52%) were re-contacted. Nine HHC (28%) showed sero-conversion and one had a skin lesion (BI negative, nested PCR positive). Periodic evaluation of HHC can contribute to the detection of infected HHC as well as new and early leprosy cases.
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One hundred years after its discovery by Carlos Chagas, American trypanosomiasis, or Chagas disease, remains an epidemiologic challenge. Neither a vaccine nor an ideal specific treatment is available for most chronic cases. Therefore, the current strategy for countering Chagas disease consists of preventive actions against the vector and transfusion-transmitted disease. Here, the present challenges, including congenital and oral transmission of Trypanosoma cruzi infections, as well as the future potential for Chagas disease elimination are discussed in light of the current epidemiological picture. Finally, a list of challenging open questions is presented about Chagas disease control, patient management, programme planning and priority definitions faced by researchers and politicians.
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Despite the wealth of information generated by trans-disciplinary research in Chagas disease, knowledge about its multifaceted pathogenesis is still fragmented. Here we review the body of experimental studies in animal models supporting the concept that persistent infection by Trypanosoma cruzi is crucial for the development of chronic myocarditis. Complementing this review, we will make an effort to reconcile seemingly contradictory results concerning the immune profiles of chronic patients from Argentina and Brazil. Finally, we will review the results of molecular studies suggesting that parasite-induced inflammation and tissue damage is, at least in part, mediated by the activities of trans-sialidase, mucin-linked lipid anchors (TLR2 ligand) and cruzipain (a kinin-releasing cysteine protease). One hundred years after the discovery of Chagas disease, it is reassuring that basic and clinical research tends to converge, raising new perspectives for the treatment of chronic Chagas disease.
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Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting formeasurement error. From the various specifications, Jöreskog and Yang's(1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance
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Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression
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Chagas disease, a neglected illness, affects nearly 12-14 million people in endemic areas of Latin America. Although the occurrence of acute cases sharply has declined due to Southern Cone Initiative efforts to control vector transmission, there still remain serious challenges, including the maintenance of sustainable public policies for Chagas disease control and the urgent need for better drugs to treat chagasic patients. Since the introduction of benznidazole and nifurtimox approximately 40 years ago, many natural and synthetic compounds have been assayed against Trypanosoma cruzi, yet only a few compounds have advanced to clinical trials. This reflects, at least in part, the lack of consensus regarding appropriate in vitro and in vivo screening protocols as well as the lack of biomarkers for treating parasitaemia. The development of more effective drugs requires (i) the identification and validation of parasite targets, (ii) compounds to be screened against the targets or the whole parasite and (iii) a panel of minimum standardised procedures to advance leading compounds to clinical trials. This third aim was the topic of the workshop entitled Experimental Models in Drug Screening and Development for Chagas Disease, held in Rio de Janeiro, Brazil, on the 25th and 26th of November 2008 by the Fiocruz Program for Research and Technological Development on Chagas Disease and Drugs for Neglected Diseases Initiative. During the meeting, the minimum steps, requirements and decision gates for the determination of the efficacy of novel drugs for T. cruzi control were evaluated by interdisciplinary experts and an in vitro and in vivo flowchart was designed to serve as a general and standardised protocol for screening potential drugs for the treatment of Chagas disease.
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Background & aims: High protein diets have been shown to improve hepatic steatosis in rodent models and in high-fat fed humans. We therefore evaluated the effects of a protein supplementation on intrahepatocellular lipids (IHCL), and fasting plasma triglycerides in obese non diabetic women.Methods: Eleven obese women received a 60 g/day whey protein supplement (WPS) for 4-weeks, while otherwise nourished on a spontaneous diet, IHCL concentrations, visceral body fat, total liver volume (MR), fasting total-triglyceride and cholesterol concentrations, glucose tolerance (standard 75 g OGTT), insulin sensitivity (HOMA IS index), creatinine clearance, blood pressure and body composition (bio-impedance analysis) were assessed before and after 4-week WPS.Results: IHCL were positively correlated with visceral fat and total liver volume at inclusion. WPS decreased significantly IHCL by 20.8 +/- 7.7%, fasting total TG by 15 +/- 6.9%, and total cholesterol by 7.3 +/- 2.7%. WPS slightly increased fat free mass from 54.8 +/- 2.2 kg to 56.7 +/- 2.5 kg, p = 0.005). Visceral fat, total liver volume, glucose tolerance, creatinine clearance and insulin sensitivity were not changed.Conclusions: WPS improves hepatic steatosis and plasma lipid profiles in obese non diabetic patients, without adverse effects on glucose tolerance or creatinine clearance. Trial Number: NCT00870077, ClinicalTrials.gov (C) 2011 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
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In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence
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Liver biopsy is the gold-standard method to stage fibrosis; however, it is an invasive procedure and is potentially dangerous. The main objective of this study was to evaluate biological markers, such as cytokines IL-13, IFN-γ, TNF-α and TGF-β, platelets, bilirubins (Bil), alanine aminotransferase (ALT) and aspartate aminotransferase (AST), total proteins, γ-glutamil transferase (γ-GT) and alkaline phosphatase (AP), that could be used to predict the severity of hepatic fibrosis in schistosomiasis and hepatitis C (HC) as isolated diseases or co-infections. The following patient groups were selected: HC (n = 39), HC/hepatosplenic schistosomiasis (HSS) (n = 19), HSS (n = 22) and a control group (n = 13). ANOVA and ROC curves were used for statistical analysis. P < 0.05 was considered significant. With HC patients we showed that TNF-α (p = 0.020) and AP (p = 0.005) could differentiate mild and severe fibrosis. With regard to necroinflammatory activity, AST (p = 0.002), γ-GT (p = 0.034) and AP (p = 0.001) were the best markers to differentiate mild and severe activity. In HC + HSS patients, total Bil (p = 0.008) was capable of differentiating between mild and severe fibrosis. In conclusion, our study was able to suggest biological markers that are non-invasive candidates to evaluate fibrosis and necroinflammatory activity in HC and HC + HSS.
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Protection against Fasciola hepatica in goats immunized with a synthetic recombinant antigen from Schistosoma mansoni fatty acid-binding protein 14 (rSm14) was investigated by assessing worm burdens, serum levels of hepatic enzymes, faecal egg count and hepatic damage, which was evaluated using gross and microscopic morphometric observation. The nature of the local immune response was assessed by examining the distribution of CD2+, CD4+, CD8+ and γ´+ T lymphocytes along with IgG+, IL-4+ and IFN-γ+ cells in the liver and hepatic lymph nodes (HLN). The goats used consisted of group 1 (unimmunized and uninfected), group 2 [infected control - immunized with Quillaia A (Quil A)] and group 3 (immunized with rSm14 in Quil A and infected), each containing seven animals. Immunization with rSm14 in Quil A adjuvant induced a reduction in gross hepatic lesions of 56.6% (p < 0.001) and reduced hepatic and HLN infiltration of CD2+, CD4+, CD8+ and γ´+ T lymphocytes as well as IL-4+ and IFN-γ+ cells (p < 0.05). This is the first report of caprine immunization against F. hepatica using a complete rSm14 molecule derived from S. mansoni. Immunization reduced hepatic damage and local inflammatory infiltration into the liver and HLN. However, considering that Quil A is not the preferential/first choice adjuvant for Sm14 immunization, further studies will be undertaken using the monophosphoryl lipid A-based family of adjuvants during clinical trials to facilitate anti-Fasciolavaccine development.
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Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.