Promotion of macrophage activation by Tie2 in the context of the inflamed synovia of rheumatoid arthritis and psoriatic arthritis patients

OBJECTIVE: To examine the role of Tie2 signalling in macrophage activation within the context of the inflammatory synovial microenvironment present in patients with RA and PsA. METHODS: Clinical responses and macrophage function were examined in wild-type and Tie2-overexpressing (Tie2-TG) mice in the K/BxN serum transfer model of arthritis. Macrophages derived from peripheral blood monocytes from healthy donors, RA and PsA patients, and RA and PsA synovial tissue explants were stimulated with TNF (10 ng/ml), angiopoietin (Ang)-1 or Ang-2 (200 ng/ml), or incubated with an anti-Ang2 neutralizing antibody. mRNA and protein expression of inflammatory mediators was analysed by quantitative PCR, ELISA and Luminex. RESULTS: Tie2-TG mice displayed more clinically severe arthritis than wild-type mice, accompanied by enhanced joint expression of IL6, IL12B, NOS2, CCL2 and CXCL10, and activation of bone marrow-derived macrophages in response to Ang-2 stimulation. Ang-1 and Ang-2 significantly enhanced TNF-induced expression of pro-inflammatory cytokines and chemokines in macrophages from healthy donors differentiated with RA and PsA SF and peripheral blood-derived macrophages from RA and PsA patients. Both Ang-1 and Ang-2 induced the production of IL-6, IL-12p40, IL-8 and CCL-3 in synovial tissue explants of RA and PsA patients, and Ang-2 neutralization suppressed the production of IL-6 and IL-8 in the synovial tissue of RA patients. CONCLUSION: Tie2 signalling enhances TNF-dependent activation of macrophages within the context of ongoing synovial inflammation in RA and PsA, and neutralization of Tie2 ligands might be a promising therapeutic target in the treatment of these diseases

Prevalência, fatores de risco e genótipos da hepatite C entre usuários de drogas

OBJECTIVE: To estimate prevalence of hepatitis C virus (HCV) infection and identify risk factors associated and circulating HCV genotypes and subtypes. METHODS: Study conducted including 691 drug users attending 26 charitable, private and public drug treatment centers in Goiânia and Campo Grande, central-western Brazil, between 2005 and 2006. Sociodemographic characteristics and risk factors for HCV infection were collected during interviews. Blood samples were tested for HCV antibodies (anti-HCV). Positive samples were submitted to HCV RNA detection by PCR with primers complementary to 5' NC and NS5B regions of viral genome and genotyped by line probe assay (LiPA) and direct nucleotide sequencing followed by phylogenetic analysis. The prevalence and odds ratio were calculated with 95% confidence intervals. Risk factors were first estimated in the univariate analysis (pOBJETIVO: Estimar la prevalencia y factores asociados a la infección por el virus de la hepatitis C en usuarios de drogas e identificar los genotipos y subtipos virales circulantes. MÉTODOS: Estudio realizado con 691 usuarios de drogas de 26 centros de tratamiento de uso de drogas filantrópicos, particulares y públicos de Goiania y Campo Grande (Centro-Oeste), entre 2005 y 2006. Datos sociodemográficos y factores de riesgo para infección por el HCV fueron obtenidos por medio de entrevistas. Muestras sanguíneas fueron evaluadas para la detección de anticuerpos para el HCV. Las muestras positivas fueron sometidas a la detección de RNA-HCV por la reacción en cadena de polimerasa con iniciadores complementarios a las regiones 5' NC y NS5B del genoma viral y genotipadas por el line probe assay (LiPA) y por secuenciación directa, seguido del análisis filogenético. Prevalencia y odds ratio fueron calculados con intervalo de 95% de confianza. Los factores de riesgo con pOBJETIVO: Estimar a prevalência e fatores associados à infecção pelo vírus da hepatite C em usuários de drogas e identificar os genótipos e subtipos virais circulantes. MÉTODOS: Estudo realizado com 691 usuários de drogas de 26 centros de tratamento de uso de drogas filantrópicos, particulares e públicos de Goiânia (GO) e Campo Grande (MS), entre 2005 e 2006. Dados sociodemográficos e fatores de risco para infecção pelo HCV foram obtidos por meio de entrevistas. Amostras sangüíneas foram testadas para a detecção de anticorpos para o HCV. As amostras positivas foram submetidas à detecção do RNA-HCV pela reação em cadeia da polimerase com iniciadores complementares às regiões 5' NC e NS5B do genoma viral e genotipadas pelo line probe assay (LiPA) e por seqüenciamento direto, seguido de análise filogenética. Prevalência e odds ratio foram calculados com intervalo de 95% de confiança. Os fatores de risco com

Fractal Characteristics of May-Grünwald-Giemsa Stained Chromatin Are Independent Prognostic Factors for Survival in Multiple Myeloma

The use of computerized image analysis for the study of nuclear texture features has provided important prognostic information for several neoplasias. Recently fractal characteristics of the chromatin structure in routinely stained smears have shown to be independent prognostic factors in acute leukemia. In the present study we investigated the influence of the fractal dimension (FD) of chromatin on survival of patients with multiple myeloma.We analyzed 67 newly diagnosed patients from our Institution treated in the Brazilian Multiple Myeloma Study Group. Diagnostic work-up consisted of peripheral blood counts, bone marrow cytology, bone radiograms, serum biochemistry and cytogenetics. The International Staging System (ISS) was used. In every patient, at least 40 digital nuclear images from diagnostic May-Grünwald-Giemsa stained bone marrow smears were acquired and transformed into pseudo-3D images. FD was determined by the Minkowski-Bouligand method extended to three dimensions. Goodness-of-fit of FD was estimated by the R(2) values in the log-log plots. The influence of diagnostic features on overall survival was analyzed in Cox regressions. Patients that underwent autologous bone marrow transplantation were censored at the day of transplantation.Median age was 56 years. According to ISS, 14% of the patients were stage I, 39% were stage II and 47% were stage III. Additional features of a bad prognosis were observed in 46% of the cases. When stratifying for ISS, both FD and its goodness-of-fit were significant prognostic factors in univariate analyses. Patients with higher FD values or lower goodness-of-fit showed a worse outcome. In the multivariate Cox-regression, FD, R(2), and ISS stage entered the final model, which showed to be stable in a bootstrap resampling study.Fractal characteristics of the chromatin texture in routine cytological preparations revealed relevant prognostic information in patients with multiple myeloma

Automatic Filtering and Substantiation of Drug Safety Signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions