Mice deficient for the fibulin-5 gene (Fbln5−/−) develop pelvic organ prolapse (POP) due to compromised elastic fibers and upregulation of matrix metalloprotease (MMP)-9. Here, we used casein zymography, inhibitor profiling, affinity pull-down, and mass spectrometry to discover additional protease upregulated in the vaginal wall of Fbln5−/− mice, herein named V1 (25 kDa). V1 was a serine protease with trypsin-like activity similar to protease, serine (PRSS) 3, a major extrapancreatic trypsinogen, was optimum at pH 8.0, and predominantly detected in estrogenized vaginal epithelium of Fbln5−/− mice. PRSS3 was (a) localized in epithelial secretions, (b) detected in media of vaginal organ culture from both Fbln5−/− and wild type mice, and (c) cleaved fibulin-5 in vitro. Expression of two serine protease inhibitors [Serpina1a (α1-antitrypsin) and Elafin] was dysregulated in Fbln5−/− epithelium. Finally, we confirmed that PRSS3 was expressed in human vaginal epithelium and that SERPINA1 and Elafin were downregulated in vaginal tissues from women with POP. These data collectively suggest that the balance between proteases and their inhibitors contributes to support of the pelvic organs in humans and mice.
RESUMOO objetivo deste estudo foi avaliar a eficiência do uso de uma rede neural artificial (RNA) para estimar o afilamento do fuste de árvores de eucalipto em sistemas silvipastoris com dois arranjos espaciais. Os dados foram provenientes de 35 árvores-amostras cubadas em sistemas silvipastoris com arranjos espaciais de 12 m x 4 m e 12 m x 2 m. Foi ajustado o modelo proposto por Garay para cada arranjo espacial. Foi treinada uma RNA de configuração Multilayer Perceptron utilizando os arranjos como variável categórica. As demais variáveis de entrada da RNA foram o diâmetro à altura do peito -1,30 m de altura, altura total, alturas de cada seção e os correspondentes diâmetros. A precisão dos métodos foi avaliada por meio das estatísticas da raiz do erro quadrático médio, correlação entre diâmetros observados e estimados, dispersão dos erros percentuais e o desvio médio absoluto. A RNA apresentou desempenho similar ao das duas funções de afilamento, demonstrando ser uma metodologia apropriada para pequenos plantios de eucalipto em sistema silvipastoril, onde pode existir restrição para o abate de árvores. PALAVRAS-CHAVE: ILPF, inteligência artificial, taper.
ABSTRACTThe aim of this study was to evaluate the efficiency of using an artificial neural network (ANN) to estimate the stem taper of eucalypt trees in a silvopastoral system composed with two spatial arrangements. The data used were collected out of 35 sample-trees scaled in a silvipastoral system with spatial arrangements of 12 m x 4 m and 12 m x 2 m. The taper model proposed by Garay was fitted for each spatial arrangement. Also, the ANN with Multilayer Perceptron configuration, using the spatial arrangement as a categorical variable, was trained. The others input variables for the ANN were the diameter at breast height -1.30 m height, total height, height of each section and the corresponding diameters. The accuracy of the methods was evaluated using the Root Mean-square Error, the correlation between observed and estimated diameters, dispersion of percentage errors and the mean absolut deviaton. The ANN achieved a similar performance compared to the two functions of tapering, proving to be an appropriate methodology for small eucalyptus plantations in silvopastoral system, where there may be restrictions for logging.
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