Disrupted hepcidin regulation in HFE-associated haemochromatosis and the liver as a regulator of body iron homoeostasis

Background The mechanisms responsible for disturbed iron homoeostasis in hereditary haemochromatosis are poorly understood. However, results of some studies indicate a link between hepcidin, a liver-derived peptide, and intestinal iron absorption, suggesting that this molecule could play a part in hepatic iron overload. To investigate this possible association, we studied the hepatic expression of the gene for hepcidin (HAMP) and a gene important in iron transport (IREG1) in patients with haemochromatosis, in normal controls, and in Hfe-knockout mice. Methods We extracted total RNA from the liver tissue of 27 patients with HFE-associated haemochromatosis, seven transplant donors (controls), and Hfe-knockout mice. HAMP and IREG1 mRNA concentrations were examined by ribonuclease protection assays and expressed relative to the housekeeping gene GAPD. Findings There was a significant decrease in HAMP expression in untreated patients compared with controls (5.4-fold, 95% CI 3.3-7.5; p

Effect of alcohol on iron storage diseases of the liver

The consumption of excess alcohol in patients with liver iron storage diseases, in particular the iron-overload disease hereditary haemochromatosis (HH), has important clinical consequences. HH, a common genetic disorder amongst people of European descent, results in a slow, progressive accumulation of excess hepatic iron. If left untreated, the condition may lead to fibrosis, cirrhosis and primary hepatocellular carcinoma. The consumption of excess alcohol remains an important cause of hepatic cirrhosis and alcohol consumption itself may lead to altered iron homeostasis. Both alcohol and iron independently have been shown to result in increased oxidative stress causing lipid peroxidation and tissue damage. Therefore, the added effects of both toxins may exacerbate the pathogenesis of disease and impose an increased risk of cirrhosis. This review discusses the concomitant effects of alcohol and iron on the pathogenesis of liver disease. We also discuss the implications of co-existent alcohol and iron in end-stage liver disease.

Evidence for a sub-morphological inflammatory process in the liver in haemochromatosis

Background/Aims: The role of cytokines in hepatic injury has been examined for many liver diseases however little is known of the cytokine involvement in haemochromatosis. The aim of the current study was to examine the hepatic gene expression of potential proinflammatory and profibrogenic cytokines in haemochromatosis. Methods: Interferon-gamma, interleukin-10, transforming growth factor-beta(1) and tumor necrosis factor-alpha mRNA expression was assessed in liver tissue from 20 haemochromatosis patients, eight controls and eight chronic hepatitis C patients. To assess the immunophenotype of the inflammatory infiltrate in haemochromatosis, liver sections were subjected to immunohistochemistry using markers for macrophages (CD68, HAM56, MAC387) or T cells (CD3 and CD45RO). Results: Interferon-gamma mRNA was increased in both haemochromatosis (0.29+/-0.08%, P=0.01) and hepatitis C patients (1.02+/-0.32%, P=0.03) compared to controls (0.04+/-0.01%). Interleukin-10 mRNA was significantly decreased in both haemochromatosis and hepatitis C patients (0.01+/-0.003%, P=0.008 and 0.03+/-0.015%, P=0.02, respectively) compared to controls (0.12+/-0.01%). CD3 positive T-cell number was significantly correlated with increasing hepatic iron concentration (r=0.56, P=0.03). Conclusions: This study has demonstrated a distinct pattern of cytokine gene expression in haemochromatosis, which resembles that of inflammatory conditions such as chronic hepatitis C. These factors may play a role in the development of iron-induced hepatic fibrosis in haemochromatosis. (C) 2003 European Association for the Study of the Liver. Published by Elsevier Science B.V. All rights reserved.

Histological alterations in liver and testis of Astyanax aff. bimaculatus caused by acute exposition to zinc

This study investigated the effect of acute exposition to zinc (Zn) on histology of the liver and testes of yellow tail lambari (Astyanax aff. bimaculatus). The exposure consisted of six concentrations of Zn (0, 3, 5, 10, 15, and 20 mg/L) for 96 hours of exposure. Fragments of liver and testis were routinely processed and embedded in plastic resin based on glycol methacrylate. Fragments of bones, muscles, liver and testis were dehydrated and digested to quantify the absorption levels of Zn in the tissue. Acute exposure to concentrations above 10mg/L has produced structural changes in the liver and gonads. The changes found in the liver were vascular congestion; decrease of cellular volume; displacement of the hepatocyte nucleus; necrosis; disarrangement of cordon structure; leukocyte infiltrate and vacuolization. The changes found in the gonads were ruptured cyst, delayed development of germ cells, pyknotic nucleus, cell cluster, displacement of cyst wall and vacuolization. The histological changes observed were compatible with the increasing concentration of zinc in environment, compromising liver and reproductive functions, because there was an increase in relative frequency of hepatocytes and reduced sperm production

A supervised versus home-based program effects on liver transplanted familial amyloidotic polyneuropathy patients: walking, fatigue and quality of life

Familial amyloidotic polyneuropathy is a systemic deposition of amyloidal fibre mainly on peripheral nervous system (but also in other systems like heart, gastrointestinal tract, kidneys, etc) and mainly produced in the liver. Purpose of this study: to evaluate the effects of a six months exercise training program(supervised or home-based) on walking capacity, fatigue and health related quality of life (HRQL) on Familial Amyloidotic Polyneuropathy patients submitted to a liver transplant.

Psychiatric assessment in transplantation

The implementation of the presumptive donor law in Brazil is expected to increase the availability of organs for transplantation. As medical management of end-stage organ dysfunction continues to improve, increasing numbers of potential transplant recipients will be available to meet this supply. There is mounting evidence that supports the involvement of skilled psychiatric practitioners in the selection of transplant candidates. Data supporting the influence of psychosocial factors on compliance and therefore medical outcomes continues to grow. The literature review allows delineating the components and rationale for comprehensive psychosocial evaluations as a component of preoperative transplantation evaluation.

Functional Assessment of Cancer Therapy Bone Marrow Transplantation: tradução e validação

OBJETIVO: Traduzir para o português e validar o questionário de qualidade de vida Functional Assessment of Cancer Therapy - Bone Marrow Transplantation (FACT-BMT) em pacientes transplantados de medula óssea. OBJETIVO: O estudo foi realizado em Ribeirão Preto, SP, em 2005. O FACT-BMT (versão 3) traduzido e a versão em português do Short Form-36 Health Survey (SF-36) foram aplicados simultaneamente em 55 pacientes consecutivos com leucemia, submetidos ao transplante e em seguimento. Dois parâmetros clínicos foram utilizados para testar a sensibilidade do questionário: tempo decorrido do transplante e presença ou não de doença do enxerto contra o hospedeiro. Foi utilizada a análise de variância (ANOVA) com o teste post hoc de Tukey. Aplicou-se o coeficiente alfa de Cronbach, padronizado para todas as questões, escore final e domínios. RESULTADOS: A média de idade dos pacientes foi 34,8±8,1 anos, com escolaridade média de 10,8±4,7 anos, sendo 78,1% do sexo feminino. A duração média de tempo pós-transplante foi de 29,8±32,19 meses. Nenhuma alteração do formato original do questionário foi observada no final do processo de tradução e adaptação cultural. A consistência interna foi alta (0,88). A correlação entre o questionário traduzido e o SF-36 variou de 0,35 a 0,57, considerada de moderada a boa para a maioria dos domínios de qualidade de vida. A avaliação das validades de construto e concorrente foi satisfatória e estatisticamente significativa. CONCLUSÕES: A versão para o português do FACT-BMT foi validada satisfatoriamente para a aplicação em pacientes brasileiros de ambos os sexos submetidos ao transplante de medula óssea.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Global and local detection of liver steatosis from ultrasound

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.