Glioblastoma is the most prevalent and malignant brain tumor identified in adults. Surgical resection followed by radiotherapy and chemotherapy, mainly with temozolomide (TMZ), is the chosen treatment for this type of tumor. However, the average survival of patients is around 15 months. Novel approaches to glioblastoma treatment are greatly needed. Here, we aimed to investigate the anti-glioblastoma effect of the combination of matteucinol (Mat) (dihydroxyflavanone derived from Miconia chamissois Naudin) with the chemotherapeutic TMZ in vitro using tumor (U-251MG) and normal astrocyte (NHA) cell lines and in vivo using the chick embryo chorioallantoic membrane (CAM) assay. The combination was cytotoxic and selective for tumor cells (28 μg/mL Mat and 9.71 μg/mL TMZ). Additionally, the combination did not alter cell adhesion but caused morphological changes characteristic of apoptosis in vitro. Notably, the combination was also able to reduce tumor growth in the chick embryo model (CAM assay). The docking results showed that Mat was the best ligand to the cell death membrane receptor TNFR1 and to TNFR1/TMZ complex, suggesting that these two molecules may be working together increasing their potential. In conclusion, Mat-TMZ can be a good candidate for pharmacokinetic studies in view of clinical use for the treatment of glioblastoma.

Abstract The Penman-Monteith equation is recommended for the estimation of reference evapotranspiration (ETo). However, it requires meteorological data that are commonly unavailable. Thus, this study evaluates artificial neural network (ANN), multivariate adaptive regression splines (MARS), and the original and calibrated Hargreaves-Samani (HS) and Penman-Monteith temperature (PMT) equations for the estimation of daily ETo using temperature. Two scenarios were considered: (i) local, models were calibrated/developed and evaluated using data from individual weather stations; (ii) regional, models were calibrated/developed using pooled data from several stations and evaluated independently in each one. Local models were also evaluated outside the calibration/training station. Data from 9 stations were used. The original PMT outperformed the original HS, but after local or regional calibrations, they performed similarly. The locally calibrated equations and the local machine learning models exhibited higher performances than their regional versions. However, the regional models had higher generalization capacity, with a more stable performance between stations. The machine learning models performed better than the equations evaluated. When comparing the ANN models with the HS equation, mean RMSE reduced from 0.96 to 0.87 and from 0.84 to 0.73, in regional and local scenarios, respectively. ANN and MARS performed similarly, with a slight advantage for ANN.

ABSTRACT It was determined by the total collection of excreta method, with broilers from 22 to 32 days of age, the coefficients of apparent metabolism of dry matter, crude protein and crude energy and apparent metabolizable energy corrected for zero nitrogen balance (AMEn) of the ethanol co-products of corn: acid oil and dried distillery grains with soluble (DDGS). The DDGS and corn acid oil presented nutritional metabolization coefficients ranging from 43 to 83% and AMEn equal 2393.5 and 7859.2kcal/kg respectively, and may be food alternatives to soybean meal and soybean oil.