Vif- H3.3 interaction, a new Vif function?

Poster presented at the EMBO Workshop- Histone variants. Strasbourg, France, 2-4 June 2014

Rs266882 polymorphism analysis in KLK3 gene by RFLPPCR in cases of prostate cancer

Poster presented at the From Basic Sciences to Clinical Research - First International Congress of CiiEM. Egas Moniz, Caparica, Portugal, 27-28 November 2015"The prostate cancer (PC) is one of the most frequent neoplasia in men even though not the deadliest. Every year more than 1,1 million men are diagnose with PC worldwide. The principal risks factors are: age, diet, familiar predisposition, race and hormones. Gleason classification is use to graduate PC based upon the histologic pattern of tumoral growth. Additionally to this classification is use TNM that allow to describe the cancer severity for each individual. Prostate-specific antigen (PSA) has been used as biomarker of PC, however it isn´t a specific marker for cancer detection. This protein is coded by KLK3 gene (located at 19q13.41) and it is regulated by androgen receptors through ligation to consensus sequences in promoter region of KLK3 – Androgen Response Elements (ARE). In ARE-I, located at -158 position, there is a single polymorphism nucleotide (SNP) named rs266882, which consists of substitution of guanine (G) for adenine (A).

Análise de polimorfismos no gene humano IGF-I

Poster apresentado nos Seminários de Ciências da Saúde, ISCSEM - Instituto Superior de Ciências da Saúde Egas Moniz, Caparica, Abril de 2013

Natalizumab Treatment Modulates Peroxisome Proliferator-Activated Receptors Expression in Women with Multiple Sclerosis

Peroxisome Proliferator-Activated Receptors (PPAR) are transcription factors suggested to be involved in inflammatory lesions of autoimmune encephalomyelitis and multiple sclerosis (MS). Our objective was to assess whether Natalizumab (NTZ) therapy is associated with alterations of PPAR expression in MS patients. We analyzed gene expression of PPAR in peripheral blood mononuclear cells (PBMC) as well as blood inflammatory markers in women with MS previously medicated with first-line immunomodulators (baseline) and after NTZ therapy. No differences in PPARα, PPARβ/δ, PPARγ, and CD36 mRNA expression were found in PBMC between patients under baseline and healthy controls. At three months, NTZ increased PPARβ/δ mRNA (p=0.009) in comparison to baseline, while mRNA expression of PPARγ and CD36 (a well-known PPAR target gene) was lower in comparison to healthy controls (p=0.026 and p=0.028, resp.). Although these trends of alterations remain after six months of therapy, the results were not statistically significant. Osteopontin levels were elevated in patients (p=0.002) and did not change during the follow-up period of NTZ treatment. These results suggest that PPAR-mediated processes may contribute to the mechanisms of action of NTZ therapy

The complete sequence of a 9000 bp fragment of the right arm of Saccharomyces cerevisiae chromosome VII contains four previously unknown open reading frames

We report the sequence of a 9000 bp fragment from the right arm of Saccharomyces cerevisiae chromosome VII. Analysis of the sequence revealed four complete previously unknown open reading frames, which were named G7587, G7589, G7591 and G7594 following standard rules for provisional nomenclature. Outstanding features of some of these proteins were the homology of the putative protein coded by G7589 with proteins involved in transcription regulation and the transmembrane domains predicted in the putative protein coded by G7591

Genome of the Avirulent Human-Infective Trypanosome—Trypanosoma rangeli

Background: Trypanosoma rangeli is a hemoflagellate protozoan parasite infecting humans and other wild and domestic mammals across Central and South America. It does not cause human disease, but it can be mistaken for the etiologic agent of Chagas disease, Trypanosoma cruzi. We have sequenced the T. rangeli genome to provide new tools for elucidating the distinct and intriguing biology of this species and the key pathways related to interaction with its arthropod and mammalian hosts.  Methodology/Principal Findings: The T. rangeli haploid genome is ,24 Mb in length, and is the smallest and least repetitive trypanosomatid genome sequenced thus far. This parasite genome has shorter subtelomeric sequences compared to those of T. cruzi and T. brucei; displays intraspecific karyotype variability and lacks minichromosomes. Of the predicted 7,613 protein coding sequences, functional annotations could be determined for 2,415, while 5,043 are hypothetical proteins, some with evidence of protein expression. 7,101 genes (93%) are shared with other trypanosomatids that infect humans. An ortholog of the dcl2 gene involved in the T. brucei RNAi pathway was found in T. rangeli, but the RNAi machinery is non-functional since the other genes in this pathway are pseudogenized. T. rangeli is highly susceptible to oxidative stress, a phenotype that may be explained by a smaller number of anti-oxidant defense enzymes and heatshock proteins.  Conclusions/Significance: Phylogenetic comparison of nuclear and mitochondrial genes indicates that T. rangeli and T. cruzi are equidistant from T. brucei. In addition to revealing new aspects of trypanosome co-evolution within the vertebrate and invertebrate hosts, comparative genomic analysis with pathogenic trypanosomatids provides valuable new information that can be further explored with the aim of developing better diagnostic tools and/or therapeutic targets

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio