Huanglongbing vector insect counting (HLB) by GAMLSS Mateus Silva Pedroso, Terezinha Aparecida Guedes, Willian Luís de Oliveira, Werica Bruna da Silva Valim, William Mario de Carvalho Nunes, et al. Acta Scientiarum Technology, 2024 Citriculture is one of the most important agricultural activities globally, with Brazil being one of the leading world producers. Thus, such activity is essential for the country's economy and the producers who depend on it. In this sense, the fight against Huanglongbing, one of the most devastating citrus diseases caused by vector insects, is essential to guarantee the quality of the fruit and avoid economic losses. The present work analyzed the counting of insect vectors in a commercial orange orchard in an observational study carried out in the municipality of Paranavaí, state of Paraná, Brazil, using the methodologies of generalized linear mixed models (GLMM) and generalized additive models for location, scale, and form (GAMLSS), with Negative Binomial probability distribution. Data were obtained by counting insects trapped in sticky traps at twelve fixed points in the orchard at three different heights and collected over seven fortnights. The results indicated that the GAMLSS model presented better results by including the linear predictor for modeling the scale parameter associated with the study factors based on the AIC criterion and diagnostic analysis tools.
Microstructured Polymer System Containing Proanthocyanidin-Enriched Extract from Limonium brasiliense as a Prophylaxis Strategy to Prevent Recurrence of Porphyromonas gingivalis Fernanda Pilatti, Raquel Isolani, Larissa Valone, Mariana Nascimento de Paula, Angelo de Oliveira Caleare, et al. Planta Medica, 2022 Periodontal diseases are a global oral health problem affecting almost 10% of the global population. Porphyromonas gingivalis is one of the main bacteria involved in the initiation and progression of inflammatory processes as a result of the action of the cysteine proteases lysin- and arginine-gingipain. Surelease/polycarbophil microparticles containing a lyophilized proanthocyanidin-enriched fraction from the rhizomes of Limonium brasiliense, traditionally named “baicuru” (ethyl acetate fraction), were manufactured. The ethyl acetate fraction was characterized by UHPLC by the presence of samarangenins A and B (12.10 ± 0.07 and 21.05 ± 0.44%, respectively) and epigallocatechin-3-O-gallate (13.44 ± 0.27%). Physiochemical aspects of Surelease/polycarbophil microparticles were characterized concerning particle size, zeta potential, entrapment efficiency, ethyl acetate fraction release, and mucoadhesion. Additionally, the presence of the ethyl acetate fraction-loaded microparticles was performed concerning potential influence on viability of human buccal KB cells, P. gingivalis adhesion to KB cells, gingipain activity, and P. gingivalis biofilm formation. In general, all Surelease/polycarbophil microparticles tested showed strong adhesion to porcine cheek mucosa (93.1 ± 4.2% in a 30-min test), associated with a prolonged release of the ethyl acetate fraction (up to 16.5 ± 0.8% in 24 h). Preincubation of KB cells with Surelease/polycarbophil microparticles (25 µg/mL) resulted in an up to 93 ± 2% reduced infection rate by P. gingivalis. Decreased activity of the P. gingivalis-specific virulence factors lysin- and arginine-gingipain proteases by Surelease/polycarbophil microparticles was confirmed. Surelease/polycarbophil microparticles decreased biofilm formation of P. gingivalis (97 ± 2% at 60 µg/mL). Results from this study prove the promising activity of Surelease/polycarbophil microparticles containing ethyl acetate fraction microparticles as a prophylaxis strategy to prevent the recurrence of P. gingivalis.
Analyzing weight evolution in mice infected by trypanosoma cruzi Breno Gabriel da Silva, Terezinha Aparecida Guedes, Vanderly Janeiro, Érika Cristina Ferreira, Silvana Marques de Araújo, et al. Acta Scientiarum Health Sciences, 2020 Concerning the specificities of a longitudinal study, the trajectories of a subject's mean responses not always present a linear behavior, which calls for tools that take into account the non-linearity of individual trajectories and that describe them towards associating possible random effects with each individual. Generalized additive mixed models (GAMMs) have come to solve this problem, since, in this class of models, it is possible to assign specific random effects to individuals, in addition to rewriting the linear term by summing unknown smooth functions, not parametrically specified, then using the P-splines smoothing technique. Thus, this article aims to introduce this methodology applied to a dataset referring to an experiment involving 57 Swiss mice infected by Trypanosoma cruzi, which had their weights monitored for 12 weeks. The analyses showed significant differences in the weight trajectory of the individuals by treatment group; besides, the assumptions required to validate the model were met. Therefore, it is possible to conclude that this methodology is satisfactory in modeling data of longitudinal sort, because, with this approach, in addition to the possibility of including fixed and random effects, these models allow adding complex correlation structures to residuals.
Linear mixed model for weight analysis in mice infected by trypanosoma cruzi Roney Peterson Pereira, Terezinha Aparecida Guedes, Érika Cristina Ferreira, Silvana Marques de Araújo, Larissa Aparecida Ricardini, et al. Acta Scientiarum Health Sciences, 2020 The use of linear mixed models for nested structure longitudinal data is called hierarchical linear modeling. This modeling takes into account the dependence of existing data within each level and between hierarchical levels. The process of modeling, estimating and analyzing diagnoses was illustrated through data on the weights of mice experimentally infected by Trypanosoma cruzi, divided into different treatment groups, with the purpose of verifying the evolution of their body weight as a result of using different types of biotherapeutics produced from Gallus gallus domesticus (chicken) serum to treat Trypanosoma cruzi. Through the model selection criteria AIC and BIC and the likelihood ratio test, a model was chosen to describe the data correctly. Model diagnoses were then performed by means of residual analysis for both levels and an analysis of influential observations to verify if any observations were signaled as influencing the fixed effects, the components of variance and the adjusted values. After the analysis, it was possible to notice that the observations that were signaled as influential had little impact on the Model chosen initially, so it was maintained, with no differences being evidenced between the treatments with the biotherapeutics tested; only the Time variable and the Random intercept were necessary to describe the weight of the mice.
Applying the generalized additive main effects and multiplicative interaction model to analysis of maize genotypes resistant to grey leaf spot C. R. L. ACORSI, T. A. GUEDES, M. M. D. COAN, R. J. B. PINTO, C. A. SCAPIM, et al. Journal of Agricultural Science, 2017 SUMMARYAnalysing the stability and adaptation of cultivars to different environments is always necessary before recommending them for planting on large areas. Additive main effects and multiplicative interaction (AMMI) models have been used to analyse genotype-by-environment interactions (G × E). AMMI models require data with homogeneous variance, normal errors and additive effects. However, agronomic data do not always conform to these statistical assumptions. The objective of the present study was to analyse G × E interactions for severity and incidence of grey leaf spot, a foliar disease in maize caused byCercospora zeae-maydis, using a generalized AMMI model. Data were collected and evaluated for 36 maize cultivars from experiments carried out in nine Brazilian regions in 2010/11 by the Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA – Milho e Sorgo). Only two of three stable genotypes defined by a quasi-likelihood model with a logistic link function could be recommended for their desirable agronomic characteristics. Four growing locations in which the genotypes were stable were identified, but in only one of these was stability associated with very severe grey leaf spot disease. Cultivars adapted to specific locations with low percentage disease severity were also identified.
Modeling asymmetric compositional data Ana Beatriz Tozzo Martins, Vanderly Janeiro, Terezinha Aparecida Guedes, Robson Marcelo Rossi, Antônio Carlos Andrade Gonçalves Acta Scientiarum Technology, 2014
Laying probability curves in quails Robson Marcelo Rossi, Elias Nunes Martins, Terezinha Aparecida Guedes, Clédina Regina Acorsi, Sebastião Gazola Acta Scientiarum Animal Sciences, 2009
