The bark of Mimosa tenuiflora (Willd.) Poiret (Leguminosae family), popularly known as “jurema preta” in Brazil, is used by the population of Contendas of Sincorá (Bahia State, Brazil) for the treatment of coughs and wound healing. Thus, the aim of this study was to evaluate the antinociceptive and anti-inflammatory activities of the bark ethanol extract (EEMT) and solvent soluble fractions (hexane—H, DCM—D, EtOAc—E and BuOH—B) of the extract in vivo. Additionally, we synthesized 5,7-dihidroxy-4’-methoxyflavanone (isosakuranetin) and isolated the compound sakuranetin, and both compounds were also tested. The anti-inflammatory and antinociceptive assays performed were: writhing test; nociception induced by intraplantar formalin injection; leukocyte recruitment to the peritoneal cavity; evaluation of vascular permeability (Evans blue test); and evaluation of mechanical hypernociception (von Frey test). Production of TNF-α, IL-10, myeloperoxidase and the expression of ICAM-1 were also evaluated. Statistical analysis was performed by one-way ANOVA followed by the Bonferroni post-test (n = 8), with P < 0.05. The EEMT showed antinociceptive activities in writhing test (100–200 mg/kg), in the second phase of the formalin test (50–200 mg/kg), and in mechanical hypernociception (100 mg/kg). EEMT showed an anti-inflammatory effect by reducing neutrophil migration to the peritoneal cavity and in the plantar tissue detected by the reduction of myeloperoxidase activity (100 mg/kg), reduction of IL-10 levels and expression of ICAM-1 in the peritoneal exudate and the mesentery (100 mg/kg), respectively. The four soluble EEMT fractions showed good results in tests for antinociceptive (H, D, E, B) and anti-inflammation (H, D, E). Only sakuranetin showed reduction of the writhing and neutrophil migration (200 mg/kg). Thus, the EEMT and soluble fractions of M. tenuiflora bark demonstrated great antinociceptive and anti-inflammatory activities, as also sakuranetin. More studies should be conducted to elucidate the mechanism of action of this compound. To the best of our knowledge, this is the first report on the antinociceptive activity of the M. tenuiflora fractions and the bioactive isolated compound sakuranetin in vivo.

Background: Point-of-care (POC) devices allow to assess HbA1c results in a single visit and facilitates the physicians’ decision making for DM control. This study aimed to assess the cost-effectiveness of POC in comparison to standard laboratory (HPLC method) for HbA1c testing in Brazilian primary care. Methods: A Markov model was developed in a 10-year time horizon for the perspective of the public health system. Effectiveness was assessed by the rate of HbA1c control after 6-months follow-up. Data were obtained from an ongoing cohort. Controlled and uncontrolled subjects were included in transition states for negative outcomes (cardiovascular diseases and complications). Probabilities and costs of transition states were extracted from a literature review. Results: Estimated annual cost for patients monitored by HPLC was U.S. $4,884.92 (SD 629.46) for an effectiveness of 0.39. For those monitored by POC, cost and effectiveness were U.S. $5,960.64 (SD 2,514.00) and 0.91, respectively. The evolution of the net monetary benefit is presented in the chart below. Conclusions: HbA1c tested by POC appears to be cost-effective in comparison with laboratory testing to improve glycemic control and prevent DM-related cardiovascular diseases and complications. Disclosure D.S. Medeiros: None. L.S. Rosa: None. S. Mistro: None. C.N. Kochergin: None. D.A. Soares: None. K.O. Silva: None. J.A. Louzado: None. M.L. Cortes: None. V.M. Bezerra: None. W.W. Amorim: None. M.G. Oliveira: None. Funding Medtronic Foundation

Background: In Brazil, the use of electronic medical records in primary care has been expanding, improving the supply of information and data storage, and allowing the analysis of various aspects and prediction of future outcomes. Aim: To develop a predictive model for the glycemic level of people with type 2 diabetes mellitus based on data from electronic medical records in primary care. Methods: Data mining techniques were applied to choose response variables and potential predictors. Afterwards, data modelling was performed using Artificial Neural Networks (ANN), which are mathematical models inspired by the neural structure of intelligent organisms that acquire knowledge through experience. They detect non-linear relationships between the response variable and the explanatory variables without these variables having been defined. Results: The highest probability of model accuracy was observed in the capillary blood glucose range between 100 and 300mg/dL. Model predictors and relative importance of each variable are shown in Figure 1. Conclusion: Applying predictive modelling to data available in primary care electronic medical records can help the early identification of individuals with difficulty in glycemic control, and increase the efficiency in the allocation of efforts to treat diabetes. Disclosure S. Mistro: None. T.V.O. Aguiar: None. V.V. Cerqueira: None. K.O. Silva: None. J.A. Louzado: None. C.N. Kochergin: None. D.A. Soares: None. W.W. Amorim: None. D.S. Medeiros: None. V.M. Bezerra: None. V.H. Carvalho: None. E. Amaro: None. M.G. Oliveira: None. M.L. Cortes: None. Funding SUS Institutional Development Support Program; Brazil Ministry of Health; Israelite Hospital; Albert Einstein (25000.028646/2018-10); Medtronic Foundation