Predictors of red blood cell transfusion after cardiac surgery: a prospective cohort study

Abstract OBJECTIVE To identify predictors of red blood cell transfusion (RBCT) after cardiac surgery. METHOD A prospective cohort study performed with 323 adults after cardiac surgery, from April to December of 2013. A data collection instrument was constructed by the researchers containing factors associated with excessive bleeding after cardiac surgery, as found in the literature, for investigation in the immediate postoperative period. The relationship between risk factors and the outcome was assessed by univariate analysis and logistic regression. RESULTS The factors associated with RBCT in the immediate postoperative period included lower height and weight, decreased platelet count, lower hemoglobin level, higher prevalence of platelet count <150x10 3/mm3, lower volume of protamine, longer duration of anesthesia, higher prevalence of intraoperative RBCT, lower body temperature, higher heart rate and higher positive end-expiratory pressure. The independent predictor was weight <66.5Kg. CONCLUSION Factors associated with RBCT in the immediate postoperative period of cardiac surgery were found. The independent predictor was weight.

Diversidade genética de populações de andiroba no Baixo Acre

O objetivo deste trabalho foi avaliar a diversidade genética em duas populações de Carapa guianensis Aubl. (andiroba), no Estado do Acre, e comparar os parâmetros de diversidade com os observados em outras populações da espécie (no Brasil: Flona Tapajós, PA, Porto Acre, AC; e na Costa Rica). Foram avaliados 77 indivíduos adultos com sete locos polimórficos de microssatélites. Observaram-se 51 alelos nas duas populações, em que o número efetivo de alelos por loco (Âe = 3,2) foi inferior ao número médio de alelos por loco (Â = 7,3), o que indica elevado número de alelos com baixa freqüência. Os valores estimados de f não diferiram de zero, o que mostra que não ocorre endogamia nas populações. A taxa de cruzamento aparente foi alta (t a = 1,11 na população Porto Acre, e t a= 0,88 na de Rio Branco), resultado indicador de que a espécie se reproduz por alogamia. Foi observado, por meio das estimativas de Â, He (diversidade gênica) e Ne (número efetivo populacional) que as populações de andiroba, comparadas neste trabalho, tiveram padrões de diversidade semelhantes, porém, proporções de alelos raros diferentes.

Constituintes químicos de Alchornea glandulosa (Euphorbiaceae)

Chemical investigation of the leaves of Alchornea glandulosa (Euphorbiaceae) afforded a mixture of b-sitosterol and stigmasterol, the terpenoid loliolide, the guanidine alkaloid N-1,N-2,N-3-triisopentenylguanidine and the phenolic compound corilagin. The structures of these compounds were elucidated by spectroscopic analysis. The antimicrobial and antiproliferative properties of the crude methanolic extract of the leaves and of fractions from its fractionation, were investigated against a series of bacteria and fungi, as well as against four human cancer cell lines.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.