Correlates of C-reactive protein levels in young adults: a population-based cohort study of 3827 subjects in Brazil

The socio-demographic, behavioral and anthropometric correlates of C-reactive protein levels were examined in a representative young adult Brazilian population. The 1982 Pelotas Birth Cohort Study (Brazil) recruited over 99% of births in the city of Pelotas that year (N = 5914). Individuals belonging to the cohort have been prospectively followed up. In 2004-2005, 77.4% of the cohort was traced, members were interviewed and 3827 individuals donated blood. Analyses of the outcome were based on a conceptual model that differentiated confounders from potential mediators. The following independent variables were studied in relation to levels of C-reactive protein in sex-stratified analyses: skin color, age, family income, education, parity, body mass index, waist circumference, smoking, fat/fiber/alcohol intake, physical activity, and minor psychiatric disorder. Geometric mean (95% confidence interval) C-reactive protein levels for the 1919 males and 1908 females were 0.89 (0.84-0.94) and 1.96 mg/L (1.85-2.09), respectively. Pregnant women and those using oral contraceptive therapies presented the highest C-reactive protein levels and all sub-groups of women had higher levels than men (P < 0.001). Significant associations between C-reactive protein levels were observed with age, socioeconomic indicators, obesity status, smoking, fat and alcohol intake, and minor psychiatric disorder. Associations were stronger at higher levels of C-reactive protein and some associations were sex-specific. We conclude that both distal (socio-demographic) and proximal (anthropometric and behavioral) factors exert strong effects on C-reactive protein levels and that the former are mediated to some degree by the latter.

Cytogenetic characterization and evaluation of c-MYC gene amplification in PG100, a new Brazilian gastric cancer cell line

Gastric cancer is the fourth most frequent type of cancer and the second cause of cancer mortality worldwide. The genetic alterations described so far for gastric carcinomas include amplifications and mutations of the c-ERBB2, KRAS, MET, TP53, and c-MYC genes. Chromosomal instability described for gastric cancer includes gains and losses of whole chromosomes or parts of them and these events might lead to oncogene overexpression, showing the need for a better understanding of the cytogenetic aspects of this neoplasia. Very few gastric carcinoma cell lines have been isolated. The establishment and characterization of the biological properties of gastric cancer cell lines is a powerful tool to gather information about the evolution of this malignancy, and also to test new therapeutic approaches. The present study characterized cytogenetically PG-100, the first commercially available gastric cancer cell line derived from a Brazilian patient who had a gastric adenocarcinoma, using GTG banding and fluorescent in situ hybridization to determine MYC amplification. Twenty metaphases were karyotyped; 19 (95%) of them presented chromosome 8 trisomy, where the MYC gene is located, and 17 (85%) presented a deletion in the 17p region, where the TP53 is located. These are common findings for gastric carcinomas, validating PG100 as an experimental model for this neoplasia. Eighty-six percent of 200 cells analyzed by fluorescent in situ hybridization presented MYC overexpression. Less frequent findings, such as 5p deletions and trisomy 16, open new perspectives for the study of this tumor.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

Characterization and classification of pequi trees (Caryocar brasiliense Camb.) based on the profile of volatile constituents using headspace solid-phase microextraction - gas chromatography - mass spectrometry and multivariate analysis

In order to determine the variability of pequi tree (Caryocar brasiliense Camb.) populations, volatile compounds from fruits of eighteen trees representing five populations were extracted by headspace solid-phase microextraction and analyzed by gas chromatography-mass spectrometry. Seventy-seven compounds were identified, including esters, hydrocarbons, terpenoids, ketones, lactones, and alcohols. Several compounds had not been previously reported in the pequi fruit. The amount of total volatile compounds and the individual compound contents varied between plants. The volatile profile enabled the differentiation of all of the eighteen plants, indicating that there is a characteristic profile in terms of their origin. The use of Principal Component Analysis and Cluster Analysis enabled the establishment of markers (dendrolasin, ethyl octanoate, ethyl 2-octenoate and β-cis-ocimene) that discriminated among the pequi trees. According to the Cluster Analysis, the plants were classified into three main clusters, and four other plants showed a tendency to isolation. The results from multivariate analysis did not always group plants from the same population together, indicating that there is greater variability within the populations than between pequi tree populations.