Search

The purpose of this study was to estimate the temporal variability of CO 2 emission (FCO 2 ) from O 2 influx into the soil (FO 2 ) in a reforested area with native vegetation in the Brazilian Cerrado, as well as to understand the dynamics of soil respiration in this ecosystem. The database is composed of soil respiration data, agroclimatic variables, improved vegetation index (EVI), and soil attributes used to train machine learning algorithms: artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS). The predictive performance was evaluated based on the mean absolute error (MEA), root mean square error (RMSE), mean absolute percentage error (MAPE), agreement index (d), confidence coefficient (c), and coefficient of determination (R 2 ). The best estimation results for validation were FCO 2 with multilayer perceptron neural network (MLP) (R 2  = 0.53, RMSE = 0.967 µmol m -2  s -1 ) and radial basis function neural network (RBF) (R 2  = 0.54, RMSE = 0.884 µmol m -2  s -1 ) and FO 2 with MLP (R 2  = 0.45, RMSE = 0.093 mg m -2  s -1 ) and RBF (R 2  = 0.74, 0.079 mg m -2  s -1 ). Soil temperature and macroporosity are important predictors of FCO 2 and FO 2 . The best combination of variables for training the ANFIS was selected based on trial and error. The results were as follows: FCO 2 (R 2  = 16) and FO 2 (R 2  = 29). In all models, FCO 2 outperformed FO 2 . A primary factor analysis was performed, and FCO 2 and FO 2 correlated best with the weather and soil attributes, respectively., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

To evaluate the genetic diversity and clustering rates of M. tuberculosis strains to better understand transmission among persons deprived of liberty (PDL) in Rio Grande do Sul (RS), southern Brazil. This is a cross-sectional study, including strains of M. tuberculosis isolated from PDL, stored at the Central Laboratory of RS, in the period from 2013 to 2018. The molecular characterization was performed using the MIRU-VNTR 15 loci method. A total of 598 M. tuberculosis strains were genotyped, and 37.5% were grouped into 53 clusters. Cluster sizes ranged from 2 to 34 strains. The largest cluster of the study had strains from 34 PDL, and 58.8% of the PDL of this cluster were in P01. Among the clusters formed, in 60.3%, there was at least one strain from P01. The most common strains in RS were LAM (53.2%) and Haarlem (31.1%). The LAM strain was the most likely to form clusters, and Haarlem was associated with anti-TB drug resistance. This was translational research, and the results can collaborate with the TB control programs, leading to improved strategies that allow the reduction of the TB burden in prisons., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Presently, several bone graft substitutes are being developed or already available for clinical use. However, the limited number of clinical and in vivo trials for direct comparison between these products may complicate this choice. One of the main reasons for this scarcity it is the use of models that do not readily allow the direct comparison of multiple bone graft substitutes, due especially to the small number of implantation sites. Although sheep cancellous bone models are now well established for these purposes, the limited availability of cancellous bone makes it difficult to find multiple comparable sites within a same animal. These limitations can be overcome by the monocortical model here proposed as it consists in 5-6 holes (5 mm Ø), in the femoral diaphysis, with similar bone structure, overlying soft tissue and loading pattern for all defects. Associated to this model, it is also described a fast histomorphometric analysis method using a computer image segmentation test (Threshold method) to assess bone regeneration parameters. The information compiled through the experimental use of 45 sheep in several studies allowed determining that this ovine model has the potential to demonstrate differences in bone-forming performance between various scaffolds. Additionally, the described histomorphometric method is fast, accurate and reproducible.