27 resultados para Non-malignant disease
em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain
Resumo:
Justificación y objetivos: El estudio PREDyCES® tuvo dos objetivos principales. Primero, analizar la prevalencia de desnutrición hospitalaria (DH) en España tanto al ingreso como al alta, y segundo, estimar sus costes asociados. Métodos: Estudio nacional, transversal, observacional, multicéntrico, en condiciones de práctica clínica habitual que evaluó la presencia de desnutrición hospitalaria al ingreso y al alta mediante el NRS-2002®. Una extensión del estudio analizó la incidencia de complicaciones asociadas a la desnutrición, el exceso de estancia hospitalaria y los costes sanitarios asociados a la DH. Resultados: La prevalencia de desnutrición observada según el NRS-2002® fue del 23.7%. El análisis multivariante mostró que la edad, el género, la presencia de enfermedad oncológica, diabetes mellitus, disfagia y la polimedicación fueron los factores principales que se asociaron a la presencia de desnutrición. La DH se asoció a un incremento de la estancia hospitalaria, especialmente en aquellos pacientes que ingresaron sin desnutrición y que presentaron desnutrición al alta (15.2 vs 8.0 días; p < 0.001), con un coste adicional asociado de 5.829€ por paciente. Conclusiones: Uno de cada cuatro pacientes en los hospitales españoles se encuentra desnutrido. Esta condición se asocia a un exceso de estancia hospitalaria y costes asociados, especialmente en pacientes que se desnutren durante su hospitalización. Se debería generalizar el cribado nutricional sistemático con el objetivo de implementar intervenciones nutricionales de conocida eficacia.
Resumo:
Recent studies have shown aberrant expression of SOX11 in various types of aggressive B-cell neoplasms. To elucidate the molecular mechanisms leading to such deregulation, we performed a comprehensive SOX11 gene expression and epigenetic study in stem cells, normal hematopoietic cells and different lymphoid neoplasms. We observed that SOX11 expression is associated with unmethylated DNA and presence of activating histone marks (H3K9/14Ac and H3K4me3) in embryonic stem cells and some aggressive B-cell neoplasms. In contrast, adult stem cells, normal hematopoietic cells and other lymphoid neoplasms do not express SOX11. Such repression was associated with silencing histone marks H3K9me2 and H3K27me3. The SOX11 promoter of non-malignant cells was consistently unmethylated whereas lymphoid neoplasms with silenced SOX11 tended to acquire DNA hypermethylation. SOX11 silencing in cell lines was reversed by the histone deacetylase inhibitor SAHA but not by the DNA methyltransferase inhibitor AZA. These data indicate that, although DNA hypermethylation of SOX11 is frequent in lymphoid neoplasms, it seems to be functionally inert, as SOX11 is already silenced in the hematopoietic system. In contrast, the pathogenic role of SOX11 is associated with its de novo expression in some aggressive lymphoid malignancies, which is mediated by a shift from inactivating to activating histone modifications.
Resumo:
The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.
Resumo:
Glioblastomas are highly diffuse, malignant tumors that have so far evaded clinical treatment. The strongly invasive behavior of cells in these tumors makes them very resistant to treatment, and for this reason both experimental and theoretical efforts have been directed toward understanding the spatiotemporal pattern of tumor spreading. Although usual models assume a standard diffusion behavior, recent experiments with cell cultures indicate that cells tend to move in directions close to that of glioblastoma invasion, thus indicating that a biasedrandom walk model may be much more appropriate. Here we show analytically that, for realistic parameter values, the speeds predicted by biased dispersal are consistent with experimentally measured data. We also find that models beyond reaction–diffusion–advection equations are necessary to capture this substantial effect of biased dispersal on glioblastoma spread
Resumo:
Background/Aims: The epidemiology of Chagas disease, until recently confined to areas of continental Latin America, has undergone considerable changes in recent decades due to migration to other parts of the world, including Spain. We studied the prevalence of Chagas disease in Latin American patients treated at a health center in Barcelona and evaluated its clinical phase. We make some recommendations for screening for the disease. Methodology/Principal Findings: We performed an observational, cross-sectional prevalence study by means of an immunochromatographic test screening of all continental Latin American patients over the age of 14 years visiting the health centre from October 2007 to October 2009. The diagnosis was confirmed by serological methods: conventional in-house ELISA (cELISA), a commercial kit (rELISA) and ELISA using T cruzi lysate (Ortho-Clinical Diagnostics) (oELISA). Of 766 patients studied, 22 were diagnosed with T. cruzi infection, showing a prevalence of 2.87% (95% CI, 1.6-4.12%). Of the infected patients, 45.45% men and 54.55% women, 21 were from Bolivia, showing a prevalence in the Bolivian subgroup (n = 127) of 16.53% (95% CI, 9.6-23.39%). All the infected patients were in a chronic phase of Chagas disease: 81% with the indeterminate form, 9.5% with the cardiac form and 9.5% with the cardiodigestive form. All patients infected with T. cruzi had heard of Chagas disease in their country of origin, 82% knew someone affected, and 77% had a significant history of living in adobe houses in rural areas. Conclusions: We found a high prevalence of T. cruzi infection in immigrants from Bolivia. Detection of T. cruzi¿infected persons by screening programs in non-endemic countries would control non-vectorial transmission and would benefit the persons affected, public health and national health systems.
Resumo:
Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.
Resumo:
Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.
Resumo:
Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to im-provement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.
Resumo:
Although metabolic syndrome (MS) and systemic lupus erythematosus (SLE) are often associated, a common link has not been identified. Using the BWF1 mouse, which develops MS and SLE, we sought a molecular connection to explain the prevalence of these two diseases in the same individuals. We determined SLE- markers (plasma anti-ds-DNA antibodies, splenic regulatory T cells (Tregs) and cytokines, proteinuria and renal histology) and MS-markers (plasma glucose, non-esterified fatty acids, triglycerides, insulin and leptin, liver triglycerides, visceral adipose tissue, liver and adipose tissue expression of 86 insulin signaling-related genes) in 8-, 16-, 24-, and 36-week old BWF1 and control New-Zealand-White female mice. Up to week 16, BWF1 mice showed MS-markers (hyperleptinemia, hyperinsulinemia, fatty liver and visceral adipose tissue) that disappeared at week 36, when plasma anti-dsDNA antibodies, lupus nephritis and a pro-autoimmune cytokine profile were detected. BWF1 mice had hyperleptinemia and high splenic Tregs till week 16, thereby pointing to leptin resistance, as confirmed by the lack of increased liver P-Tyr-STAT-3. Hyperinsulinemia was associated with a down-regulation of insulin related-genes only in adipose tissue, whereas expression of liver mammalian target of rapamicyn (mTOR) was increased. Although leptin resistance presented early in BWF1 mice can slow-down the progression of autoimmunity, our results suggest that sustained insulin stimulation of organs, such as liver and probably kidneys, facilitates the over-expression and activity of mTOR and the development of SLE.
Resumo:
Objectives: General population studies have shown associations between copy number variation (CNV) of the LPA gene Kringle-IV type-2 (KIV-2) coding region, single-nucleotide polymorphism (SNP) rs6415084 in LPA and coronary heart disease (CHD). Because risk factors for HIV-infected patients may differ from the general population, we aimed to assess whether these potential associations also occur in HIV-infected patients. Methods: A unicenter, retrospective, case-control (1:3) study. Eighteen HIV-patients with confirmed diagnosis of acute myocardial infarction (AMI) were adjusted for age, gender, and time since HIV diagnosis to 54 HIV-patients without CHD. After gDNA extraction from frozen blood, both CNV and SNP genotyping were performed using real-time quantitative PCR. All genetic and non-genetic variables for AMI were assessed in a logistic regression analysis. Results: Our results did not confirm any association in terms of lipoprotein(a) LPA structural genetic variants when comparing KIV-2 CNV (p = 0.67) and SNP genotypes (p = 0.44) between AMI cases and controls. However, traditional risk factors such as diabetes mellitus, hypertension, and CD4(+) T cell count showed association (p < 0.05) with CHD. Conclusion: Although significant associations of AMI with diabetes, hypertension and CD4(+) T cell count in HIV-patients were found, this study could not confirm the feasibility neither of KIV-2 CNV nor rs6415084 in LPA as genetic markers of CHD in HIV-infected patients.Highlights:● Individuals with HIV infection are at higher risk of coronary heart disease (CHD) than the non-infected population.● Our results showed no evidence of LPA structural genetic variants associated with CHD in HIV-1-infected patients.● Associations were found between diabetes mellitus, arterial hypertension, CD4(+) T cell count, and CHD.● The clinical usefulness of these biomarkers to predict CHD in HIV-1-infected population remains unproven.● Further studies are needed to assess the contribution of common genetic variations to CHD in HIV-infected individuals.
Resumo:
Introduction: The coexistence of different molecular types of classical protease-resistant prion protein in the same individual have been described, however, the simultaneous finding of these with the recently described protease-sensitive variant or variably protease-sensitive prionopathy has, to the best of our knowledge, not yet been reported. Case presentation: A 74-year-old Caucasian woman showed a sporadic Creutzfeldt-Jakob disease clinical phenotype with reactive depression, followed by cognitive impairment, akinetic-rigid Parkinsonism with pseudobulbar syndrome and gait impairment with motor apraxia, visuospatial disorientation, and evident frontal dysfunction features such as grasping, palmomental reflex and brisk perioral reflexes. She died at age 77. Neuropathological findings showed: spongiform change in the patient"s cerebral cortex, striatum, thalamus and molecular layer of the cerebellum with proteinase K-sensitive synaptic-like, dot-like or target-like prion protein deposition in the cortex, thalamus and striatum; proteinase K-resistant prion protein in the same regions; and elongated plaque-like proteinase K-resistant prion protein in the molecular layer of the cerebellum. Molecular analysis of prion protein after proteinase K digestion revealed decreased signal intensity in immunoblot, a ladder-like protein pattern, and a 71% reduction of PrPSc signal relative to non-digested material. Her cerebellum showed a 2A prion protein type largely resistant to proteinase K. Genotype of polymorphism at codon 129 was valine homozygous. Conclusion: Molecular typing of prion protein along with clinical and neuropathological data revealed, to the best of our knowledge, the first case of the coexistence of different protease-sensitive prion proteins in the same patient in a rare case that did not fulfill the current clinical diagnostic criteria for either probable or possible sporadic Creutzfeldt-Jakob disease. This highlights the importance of molecular analyses of several brain regions in order to correctly diagnose rare and atypical prionopathies
Resumo:
Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to improvement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.
Resumo:
The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.
Resumo:
Abstract: Since ancient times, people have attributed a variety of health benefits to moderate consumption of fermented beverages such as wine and beer, often without any scientific basis. There is evidence that excessive or binge alcohol consumption is associated with increased morbidity and mortality, as well as with work related and traffic accidents. On the contrary, at the moment, several epidemiological studies have suggested that moderate consumption of alcohol reduces overall mortality, mainly from coronary diseases. However, there are discrepancies regarding the specific effects of different types of beverages (wine, beer and spirits) on the cardiovascular system and cancer, and also whether the possible protective effects of alcoholic beverages are due to their alcoholic content (ethanol) or to their non-alcoholic components (mainly polyphenols). Epidemiological and clinical studies have pointed out that regular and moderate wine consumption (one to two glasses a day) is associated with decreased incidence of cardiovascular disease (CVD), hypertension, diabetes, and certain types of cancer, including colon, basal cell, ovarian, and prostate carcinoma. Moderate beer consumption has also been associated with these effects, but to a lesser degree, probably because of beer"s lower phenolic content. These health benefits have mainly been attributed to an increase in antioxidant capacity, changes in lipid profiles, and the anti-inflammatory effects produced by these alcoholic beverages. This review summarizes the main protective effects on the cardiovascular system and cancer resulting from moderate wine and beer intake due mainly to their common components, alcohol and polyphenols.