Background: The search for sickle cell disease (SCD) prognosis biomarkers is a challenge. These markers identification can help to establish further therapy, later severe clinical complications and with patients follow-up. We attempted to study a possible involvement of levels of high-density lipoprotein cholesterol (HDL-C) in steady-state children with SCD, once that this lipid marker has been correlated with anti-inflammatory, anti-oxidative, anti-aggregation, anti-coagulant and pro-fibrinolytic activities, important aspects to be considered in sickle cell disease pathogenesis.Methods: We prospectively analyzed biochemical, inflammatory and hematological biomarkers of 152 steady-state infants with SCD and 132 healthy subjects using immunochemistry, immunoassay and electronic cell counter respectively. Clinical data were collected from patient medical records.Results: Of the 152 infants investigated had a significant positive association of high-density lipoprotein cholesterol with hemoglobin (P < 0.001), hematocrit (P < 0.001) and total cholesterol (P < 0.001) and a negative significant association with reticulocytes (P = 0.046), leukocytes (P = 0.015), monocytes (P = 0.004) and platelets (P = 0.005), bilirubins [total bilirubin (P < 0.001), direct bilirubin (P < 0.001) and indirect bilirubin (P < 0.001], iron (P < 0.001), aminotransferases [aspartate aminotransferase (P = 0.004), alanine aminotransferase (P = 0.035)], lactate dehydrogenase (P < 0.001), urea (P = 0.030), alpha 1-antitrypsin (P < 0.001), very low-density lipoprotein cholesterol (P = 0.003), triglycerides (P = 0.005) and hemoglobin S (P = 0.002). Low high-density lipoprotein cholesterol concentration was associated with the history of cardiac abnormalities (P = 0.025), pneumonia (P = 0.033) and blood transfusion use (P = 0.025). Lipids and inflammatory markers were associated with the presence of cholelithiasis.Conclusions: We hypothesize that some SCD patients can have a specific dyslipidemic subphenotype characterized by low HDL-C with hypertriglyceridemia and high VLDL-C in association with other biomarkers, including those related to inflammation. This represents an important step toward a more reliable clinical prognosis. Additional studies are warranted to test this hypothesis and the probably mechanisms involved in this complex network of markers and their role in SCD pathogenesis.

Residents of urban slums are at greater risk for disease than their non-slum dwelling urban counterparts. We sought to contrast the prevalences of selected non-communicable diseases (NCDs) between Brazilian adults living in a slum and the general population of the same city, by comparing the age and sex-standardized prevalences of selected NCDs from a 2010 survey in Pau da Lima, Salvador Brazil, with a 2010 national population-based telephone survey. NCD prevalences in both populations were similar for hypertension (23.6% (95% CI 20.9–26.4) and 22.9% (21.2–24.6), respectively) and for dyslipidemia (22.7% (19.8–25.5) and 21.5% (19.7–23.4)). Slum residents had higher prevalences of diabetes mellitus (10.1% (7.9–12.3)) and of overweight/obesity (46.5% (43.1–49.9)), compared to 5.2% (4.2–6.1) and 40.6% (38.5–42.8) of the general population in Salvador. Fourteen percent (14.5% (12.1–17.0)) of slum residents smoked cigarettes compared to 8.3% (7.1–9.5) of the general population in Salvador. The national telephone survey underestimated the prevalence of diabetes mellitus, overweight/obesity, and smoking in the slum population, likely in part due to differential sampling inside and outside of slums. Further research and targeted policies are needed to mitigate these inequalities, which could have significant economic and social impacts on slum residents and their communities.

Interventions via the Internet are promising regarding the promotion of healthy habits among youth. The objective of this study was to evaluate the effect of an adapted version of StayingFit to promote healthy eating habits and the measurement adequacy of anthropometric markers among adolescents. A web school-based 12-month cluster-randomized controlled trial examining 7th to 9th grade students was conducted in twelve schools in Salvador, Bahia, Brazil. The schools’ students were randomly distributed into the intervention and control groups. The intervention group participated in StayingFit, an online program designed to encourage and guide healthy eating habits and control body weight. Data on food consumption, anthropometry, physical activity level, and sedentary behavior were collected from all of the students at the beginning of and after the 12-month study. Demographic and socioeconomic data were collected at baseline. The baseline data indicated high rates of overweight (14.4% overweight and 8.5% obese), insufficiently active (87.6%), and sedentary (63.7%). Furthermore, few adolescents regularly consumed fruits (18.8%) and vegetables/legumes (16.4%). Generalized estimating equations (GEEs) were used to evaluate the effect of the intervention. At the end of the follow-up period, students in the intervention group had a 43% increased chance of regularly consuming beans (OR = 1.43, 95% CIs = 1.10–1.86) and a 35% decreased chance of regularly consuming soft drinks (OR = 0.65, 95% CIs = 0.50–0.84). No differences were found between the groups studied with regard to the anthropometric parameters. Despite these modest results, the implementation of a web intervention can be beneficial and help promote positive changes in adolescent eating habits.

Aim This study aimed to verify the correlation between murine measurements and retroperitoneal adipose tissue in rats exposed to the high-fat diet. Material and methods: Wistar male adult rats, descendants of mothers who consumed a high-fat diet during pregnancy and lactation and fed the same diet after weaning were used. At 60 days of life, body weight, longitudinal axis and waist circumference (WC) were measured. The Body Mass Index (BMI) and the Lee Index were calculated for a posterior analysis of the correlation with the amount of retroperitoneal adipose tissue dissected on the same day. For analysis of the data, the Pearson correlation test was used, considering statistical significance for p <0.05. Results: Body weight had a weak correlation (r= 0.31; p= 0.38) with retroperitoneal adipose tissue. While the longitudinal correlated moderately and negative (r= -0.40; p= 0.25). Abdominal circumference (r= 0.62; p= 0.05), body mass index (r= 0.61; p= 0.03) and Lee (r= 0.69; p= 0.03) correlated moderately and positively with adipose tissue. Conclusion: Among the measured murine measurements, weight and longitudinal axis were not good indicators to represent accumulation of retroperitoneal adipose tissue in rats. However, Lee's index seems to be the best murine marker to diagnose the accumulation of retroperitoneal fat. BMI, CA and Lee index were murine parameters with higher correlation.

Objective: To review the literature on the use of urinary cotinine as a biological marker of cigarette smoke exposure. Methods: Narrative review of original and review articles on the topic of interest, published in Portuguese or English by June 2018, and selected in the following online databases: PubMed and Virtual Health Library (VHL). Results: Urinary cotinine is usually the recommended biomarker to estimate exposure to cigarette smoke, and can be used alone or, preferably, in association with questionnaires. Different analytical techniques can be used to quantify urinary cotinine and are differently performed because of urine sample interfering factors. Conclusion: The precise classification of smoking status is essential. It is advisable to use objective measurements regarding smoking habits since self-reported smoking may not always represent the true smoking status of the individual, particularly in groups that are more vulnerable to omitting the information of questionnaries, in addition, it has possible biases of memory. The accurate assessment of smoking is crucial to improve clinical management and counseling for different diseases as well as the establishment of preventive strategies. So, the use of urinary cotinine as a biomarker of cigarette smoke exposure seems to be a suitable assay to distinguish non-smokers from passive and active smokers.