p53 modeling as a route to mesothelioma patients stratification and novel therapeutic identification

Background Malignant pleural mesothelioma (MPM) is an orphan disease that is difficult to treat using traditional chemotherapy, an approach which has been effective in other types of cancer. Most chemotherapeutics cause DNA damage leading to cell death. Recent discoveries have highlighted a potential role for the p53 tumor suppressor in this disease. Given the pivotal role of p53 in the DNA damage response, here we investigated the predictive power of the p53 interactome model for MPM patients’ stratification. Methods We used bioinformatics approaches including omics type analysis of data from MPM cells and from MPM patients in order to predict which pathways are crucial for patients’ survival. Analysis of the PKT206 model of the p53 network was validated by microarrays from the Mero-14 MPM cell line and RNA-seq data from 71 MPM patients, whilst statistical analysis was used to identify the deregulated pathways and predict therapeutic schemes by linking the affected pathway with the patients’ clinical state. Results In silico simulations demonstrated successful predictions ranging from 52 to 85% depending on the drug, algorithm or sample used for validation. Clinical outcomes of individual patients stratified in three groups and simulation comparisons identified 30 genes that correlated with survival. In patients carrying wild-type p53 either treated or not treated with chemotherapy, FEN1 and MMP2 exhibited the highest inverse correlation, whereas in untreated patients bearing mutated p53, SIAH1 negatively correlated with survival. Numerous repositioned and experimental drugs targeting FEN1 and MMP2 were identified and selected drugs tested. Epinephrine and myricetin, which target FEN1, have shown cytotoxic effect on Mero-14 cells whereas marimastat and batimastat, which target MMP2 demonstrated a modest but significant inhibitory effect on MPM cell migration. Finally, 8 genes displayed correlation with disease stage, which may have diagnostic implications. Conclusions Clinical decisions related to MPM personalized therapy based on individual patients’ genetic profile and previous chemotherapeutic treatment could be reached using computational tools and the predictions reported in this study upon further testing in animal models

Prevalência e fatores associados ao tabagismo em estudantes de medicina de uma universidade em Passo Fundo (RS) Prevalence of and variables related to smoking among medical students at a university in the city of Passo Fundo, Brazil

OBJETIVO: Verificar a prevalência e fatores associados ao tabagismo entre os acadêmicos de medicina e avaliar o perfil desse grupo. MÉTODOS: Responderam a um questionário autoaplicável, contendo perguntas sobre consumo e atitudes relacionadas ao tabagismo, 316 acadêmicos de medicina (98,7% do total) da Universidade de Passo Fundo. Segundo recomendações da Organização Mundial da Saúde, os estudantes foram classificados em fumantes diários, fumantes ocasionais, ex-fumantes ou não-fumantes, sendo considerados fumantes ativos os nas duas primeiras categorias. RESULTADOS: Observou-se que 16,5% dos acadêmicos eram fumantes ativos (5,4% diários e 11,1% ocasionais) e 3,5% eram ex-fumantes. A média de idade foi 22,2 ± 2,4 anos. Os fatores significativamente associados ao tabagismo (p < 0,05) foram sexo masculino, pai fumante, uso regular de bebidas alcoólicas e uso de antidepressivos ou ansiolíticos. Verificou-se que 69,2% dos fumantes iniciaram o tabagismo entre 15 e 19 anos, tendo como principais motivações a vontade própria e/ou a influência de amigos. A conceituação do tabagismo como doença foi significativamente maior entre os não-fumantes. Quanto à carga tabágica, 70,6% dos fumantes consumiam 1-10 cigarros por dia. Entre os fumantes, 67,3% já tentaram parar de fumar, 96,0% acreditam serem capazes de fazê-lo e 87,2% pretendem deixar de fumar, ao passo que 92,3% admitiram que o cigarro faz mal à saúde. CONCLUSÕES: A prevalência do tabagismo ainda é significativa entre os acadêmicos de medicina, sendo fundamental estabelecer estratégias preventivas e de cessação mais efetivas a fim de se tentar reduzir o número de fumantes entre os futuros médicos.<br>OBJECTIVE:To determine the prevalence of and factors associated with smoking among medical students, as well as to evaluate the profile of this group. METHODS: A total of 316 medical students (98.7% of the total) at the University of Passo Fundo, in the city of Passo Fundo, Brazil, completed a self-report questionnaire with questions on tobacco intake and on attitudes related to smoking. In accordance with the World Health Organization guidelines, the students were classified as daily smokers, occasional smokers, former smokers or nonsmokers, those in the two first categories being considered active smokers. RESULTS: We found that 16.5% of the students were active smokers (daily smokers, 5.4%; occasional smokers, 11.1%) and that 3.5% were former smokers. The mean age was 22.2 ± 2.4 years. Factors significantly associated with the smoking habit (p < 0.05) were male gender, paternal smoking, regular alcohol consumption and use of antidepressants or anxiolytics. For the majority (69.2%) of the smokers, the age at smoking onset was 15-19 years of age, and the main motivations to start smoking were selfinitiative and influence of friends. The conceptualization of smoking as an illness was significantly higher among the nonsmokers. In 70.6% of the smokers, tobacco intake was 1-10 cigarettes a day. Among the smokers, 92.3% agreed that smoking is harmful to health, 67.3% had tried to quit smoking, 96.0% believed themselves able to do so, and 87.2% intended to quit smoking. CONCLUSIONS: The prevalence of smoking remains significant among medical students. Therefore, it is fundamental that we develop more effective strategies for smoking prevention and cessation in order to reduce the number of smokers among future doctors

From grasping to complex imitation: mirror systems on the path to language

Mirror system hypothesis, Brain evolution, Language evolution, Primate evolution, Neural models, Imitation, Mirror neurons, Sequential behavior,