Interesse e práticas relacionadas à oncologia ginecológica entre os membros da federação brasileira de associações de ginecologia e obstetrícia

Objective The present study aims to obtain basic demographic information, the level of interest and of training in gynecology oncology among Brazilian obstetricians and gynecologists (OB-GYNs) to create a professional profile. Methods An online questionnaire was sent to 16,008 gynecologists affiliated to the Brazilian Federation of Associations of Gynecology and Obstetrics (FEBRASGO, in the Portuguese acronym). We considered gynecologists dedicated to gynecologic oncology (OB-GYNs ONCO) those who self-reported that > 50% of their daily practice consists in working with women's cancer care. Results A total of 1,608 (10%) of 16,008 FEBRASGO members responded. The OB-GYNs are concentrated in the southern and southeastern states of Brazil. Gynecologic oncology was considered the 8th greatest area of interest in gynecology among the OB-GYNs. A total of 95 (5.9%) of the OB-GYNs were considered OB-GYNs ONCO. Obstetricians and gynecologists are actively engaged in cancer care: > 60% of them dedicate up to 25% of their daily practice to oncology. The role of the physicians in screening and prevention, diagnosis, in the treatment of precancerous lesions, and in low complexity surgical procedures is notably high. Gynecologists dedicated to gynecologic oncology in Brazil have a heterogeneous, nonstandardized and short training period in gynecologic oncology. These professionals had a more significantly role in performing medium- and high-complexity operations compared with OB-GYNs (65.2% versus 34%, and 47.3% versus 8.4%, respectively). Conclusion The role of OB-GYNs and of OB-GYNs ONCO appears to be complementary. Obstetricians and gynecologists act more often in screening and prevention and in low-complexity surgical procedures, whereas OB-GYNs ONCO are more involved in highly complex cases. Strategies to raise standards in cancer training and to encourage the recognition of gynecologic oncology as a subspecialty should be adopted in Brazil416394399Objetivo O presente estudo tem como objetivo obter informações demográficas básicas, o nível de interesse e de treinamento em ginecologia oncológica entre obstetras e ginecologistas (OB-GYNs) brasileiros para criar um perfil destes profissionais. Métodos Um questionário online foi enviado a 16.008 ginecologistas filiados à Federação Brasileira de Associações de Ginecologia e Obstetrícia (FEBRASGO). Nós consideramos ginecologistas dedicados à oncologia ginecológica (OB-GYNs ONCO) aqueles que referiram atuar em > 50% de sua prática diária com o tratamento do câncer feminino. Resultados Um total de 1.608 (10%) dos 16.008 membros da FEBRASGO responderam ao questionário. Os OB-GYNs estão concentrados nos estados do sul e sudeste do Brasil. A oncologia ginecológica foi considerada a 8ª área de maior interesse em ginecologia entre os OB-GYNs. Um total de 95 (5,9%) dos OB-GYNs foram considerados ginecologistas dedicados à oncologia ginecológica (OB-GYNs ONCO). Obstetras e ginecologistas estão ativamente envolvidos no tratamento do câncer: > 60% deles dedicam até 25% de sua prática diária à oncologia. O papel dos médicos na triagem e na prevenção, no diagnóstico, no tratamento de lesões pré-cancerosas e em procedimentos cirúrgicos de baixa complexidade é notavelmente alto. Ginecologistas dedicados à oncologia ginecológica no Brasil têm um período de treinamento em oncologia ginecológica heterogêneo, não padronizado e curto. Estes profissionais tiveram um papel mais significativo na realização de operações de média e alta complexidade em comparação com OB-GYNs (65,2% versus 34%, e 47,3% versus 8,4%, respectivamente). Conclusão Os papéis dos OB-GYN e dos OB-GYNs ONCO parecem ser complementares. Os OB-GYNs frequentemente atuam em triagem e prevenção e em procedimentos cirúrgicos de baixa complexidade, enquanto os OB-GYNs ONCO estão mais envolvidos em casos de mais alta complexidade. Estratégias para elevar os padrões de treinamento em oncoginecologia e incentivar o reconhecimento da oncologia ginecológica como uma subespecialidade devem ser adotadas no Brasil

Espectroscopia de Energia Dispersiva (EDS) associada à Análise de Componentes Principais (PCA) para análise de composição elementar e comparação de alfaces do tipo crespa (Lactuca Sativa L.) de cultivo orgânico e convencional

A alface crespa (Lactuca sativa L.) é uma das hortaliças folhosas mais cultivadas e consumidas em diversos países. A Organização Mundial de Saúde (OMS) incentiva o consumo de hortaliças e frutas, uma vez que estas são importantes para compor uma dieta saudável. Nos últimos anos a procura por produtos orgânicos aumentou significativamente, pois dispõe de alimentos mais valorizados e de maior qualidade em relação ao sabor e procedência. Técnicas espectroscópicas associadas a ferramentas estatísticas tem sido frequentemente usadas na indústria alimentícia, com elas pode-se obter de maneira rápida e precisa informações estruturais e elementares das amostras, a fim de compará-las. O presente trabalho utiliza a Espectroscopia por Dispersão em Energia (EDS) associada à análise de componentes principais (PCA) para obter a composição elementar, e comparar/discriminar grupos de amostras de alfaces crespa de cultivo orgânico e convencional. Foram encontrados os elementos Na, Mg, P, K, Ca, Cl, S, Al e Si, nas amostras, e ao realizar a PCA observou-se que as amostras de cultivo orgânicas e convencional adquiridas no hipermercado estão bem próximas da amostra de referência, orgânica

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Characterization of a novel sugar transporter involved in sugarcane bagasse degradation in Trichoderma reesei

Abstract Background Trichoderma reesei is a saprophytic fungus implicated in the degradation of polysaccharides present in the cell wall of plants. T. reesei has been recognized as the most important industrial fungus that secretes and produces cellulase enzymes that are employed in the production of second generation bioethanol. A few of the molecular mechanisms involved in the process of biomass deconstruction by T. reesei; in particular, the effect of sugar transporters and induction of xylanases and cellulases expression are yet to be known. Results In our study, we characterized a novel sugar transporter, which was previously identified by our group through in silico analysis of RNA-seq data. The novel T. reesei 69957-sugar transport system (Tr69957) is capable of transporting xylose, mannose, and cellobiose using a T. reesei 69957-sugar transport system in Saccharomyces cerevisiae. The deletion of Tr69957 in T. reesei affected the fungal growth and biomass accumulation, and the sugar uptake in the presence of mannose, cellobiose, and xylose. Molecular docking studies revealed that Tr69957 shows reduced protein–ligand binding energy for interactions towards disaccharides in comparison with monosaccharides. Furthermore, the deletion of Tr69957 affected the gene expression of cellobiohydrolases (cel7a and cel6a), β-glucosidases (cel3a and cel1a), and xylanases (xyn1 and xyn2) in the cultures of parental and mutant strains in the presence of cellobiose and sugarcane bagasse (SCB). Conclusion The transporter Tr69957 of T. reesei can transport cellobiose, xylose, and mannose, and can affect the expression of a few genes encoding enzymes, such as cellulases and xylanases, in the presence of SCB. We showed for the first time that a filamentous fungus (T. reesei) contains a potential mannose transporter that may be involved in the degradation of cellulose

Selecting tropical wheat genotypes through combining ability analysis

Abstract The selection of parents to originate promising base populations, as well as the knowledge of the gene effects controlling agronomic traits by means of diallel, are useful to drive genetic gains in Brazilian tropical wheat breeding programs. The goals of this study were to select tropical wheat parents with a high frequency of favorable alleles and segregating populations with high potential to originate superior progenies through partial diallel analysis. Thus, 14 parents were divided in two groups and crossed in a 7 × 7 partial diallel scheme to originate 49 F1 combinations. After obtaining F2 generation, the populations and the parents were evaluated in the field in the summer of 2021. Days for heading, plant height, rust and yellow spot resistance, and grain yield were evaluated. The data were subjected to partial diallel analysis. There were significant effects of general combining ability for all traits. The specific combining ability effect was significant for days for heading and plant height. The additive gene effects were predominant over the non-additive ones. The parents with the highest frequency of favorable alleles for the traits evaluated were selected in each group. Four populations with high genetic potential to originate superior progenies were selected

Spectral Method for Liming Recommendation in Oxisol Based on the Prediction of Chemical Characteristics Using Interval Partial Least Squares Regression

Thousands of chemical analyses are carried out annually with the aim of recommending soil correction; however, these analyses are expensive, destructive, time-consuming, and can be harmful to the environment. As an alternative to conventional analysis methods, diffuse reflectance spectroscopy has been proposed as an option for evaluating the chemical characteristics of soil. The selection of variables has also emerged as an alternative to improve the performance of PLSR (partial least squares regression), as it decreases the root mean square error (RMSE) and increases the accuracy of the models. However, few studies have used a previous selection of variables for the construction of PLSR models to estimate the chemical characteristics of soil. In this context, the hypothesis in this study was that it is possible to calculate the liming recommendation in Oxisol based on the chemical characteristics estimated by PLSR, with a previous selection of variables using iPLS (Interval PLS). The objective was to calculate the need for liming based on chemical characteristics estimated via iPLS selection and PLSR modeling of specific wavelengths of soil reflectance. The experimental area was treated with different application rates of limestone, with and without incorporation, and phosphogypsum was applied in additional treatments. Soil assessments were carried out 5, 12, 24, and 36 months after the application of the treatments, using six layers: 0.00–0.05, 0.05–0.10, 0.10–0.20, 0.20–0.30, 0.30–0.40 and 0.40–0.60 m. Samples were subjected to conventional laboratory analyses, and spectral readings (400–2500 nm) were obtained with a spectroradiometer. The spectral curves were subjected to the iPLS variable selection method to generate PLSR models of the chemical characteristics used to calculate the liming recommendation. The chemical characteristics of the soil, such as Ca2+, sum of bases (SB), effective cation exchange capacity (CTCe), cation exchange capacity (CTC), and base saturation (BS), could be estimated, with values of R2 ranging from 0.83 to 0.92 in the calibration and validation steps, and from 0.84 to 0.90 for the prediction step (in the fourth assessment). The liming recommendation calculated based on the chemical characteristics predicted from the PLSR models showed a strong correlation (r > 0.86) with the liming recommendation calculated by conventional laboratory techniques. The fourth soil assessment yielded the best correlation coefficient (r = 0.95)