Search

While prime editing is a promising technique, some genomic sites remain difficult to edit. Here the authors present fluoPEER, fluorescent prime editing and enrichment reporter, to rank the efficiency of pegRNAs and prime editor variants.

Nickel-based superalloys, namely INCONEL® variants, have had an increase in applications throughout various industries like aeronautics, automotive and energy power plants. These superalloys can withstand high-temperature applications without suffering from creep, making them extremely appealing and suitable for manufactured goods such as jet engines or steam turbines. Nevertheless, INCONEL® alloys are considered difficult-to-cut materials, not only due to their superior material properties but also because of their poor thermal conductivity (k) and severe work hardening, which may lead to premature tool wear (TW) and poor final product finishing. In this regard, it is of paramount importance to optimise the machining parameters, to strengthen the process performance outcomes concerning the quality and cost of the product. The present review aims to systematically summarize and analyse the progress taken within the field of INCONEL® machining sensitively over the past five years, with some exceptions, and present the most recent solutions found in the industry, as well as the prospects from researchers. To accomplish this article, ScienceDirect, Springer, Taylor & Francis, Wiley and ASME have been used as sources of information as a result of great fidelity knowledge. Books from Woodhead Publishing Series, CRC Press and Academic Press have been also used. The main keywords used in searching information were: “Nickel-based superalloys”, “INCONEL® 718”, “INCONEL® 625” “INCONEL® Machining processes” and “Tool-wear mechanisms”. The combined use of these keywords was crucial to filter the huge information currently available about the evolution of INCONEL® machining technologies. As a main contribution to this work, three SWOT analyses are provided on information that is dispersed in several articles. It was found that significant progress in the traditional cutting tool technologies has been made, nonetheless, the machining of INCONEL® 718 and 625 is still considered a great challenge due to the intrinsic characteristics of those Ni-based-superalloys, whose machining promotes high-wear to the tools and coatings used.

The Brazilian National Institute for Space Research (INPE) produces official information about deforestation as well as land use and cover in the country, based on remote sensing images. The current open data policy adopted by many space agencies and governments worldwide provided access to petabytes of remote sensing images. To properly deal with this vast amount of images, novel technologies have been proposed and developed based on cloud computing and big data systems. This paper describes the INPE’s initiatives in using remote sensing images and cloud services of the Amazon Web Services (AWS) infrastructure to improve land use and cover monitoring.

Meteorological conditions characterize the southern Brazilian coast a cyclogenetic area. The current study seeks to analyse the sensitivity of the WRF model to initial and boundary meteorological conditions in the simulation of an extratropical cyclone that occurred on the southern Brazilian coast on October 28, 2018. For this purpose, the WRF model was set up for two experimental simulations using the NCEP FNL and the NCEP CFSv2 reanalysis data as initial/boundary conditions. The sensitivity analysis was carried out with the cyclone trajectory assessment and comparison with wind speed data from meteorological stations. The results show that the initial meteorological conditions significantly influence the simulation of the cyclone track. In a nutshell, the use of NCEP CFSv2 resulted in more accurate wind speed simulations when compared to the values observed in the stations. With correlation coefficient values around 0.7, and the lowest bias (−2.57 m/s) and RMSE (3.68 m/s). In contrast, using the NCEP FNL data, the lowest correlation coefficient and the highest bias and RMSE values were obtained: 0.58, −3.97 m/s and 4.91 m/s, respectively. However, both simulations tend to underestimate observational wind speed values. The superior performance of simulations using CFSv2 tends to be related to the finer horizontal resolution of this reanalysis data source.

O Psidium (P.) guineense Swartz (Myrtaceae) é uma planta nativa da região tropical das Américas, no Brasil encontra-se distribuída em regiões do litoral; seu perfil fitoquímico descreve a planta medicinal com potencial farmacológico no tratamento de infecções do trato gastrointestinal e geniturinário. O presente estudo busca realizar a análise do potencial genotóxico do extrato metanólico da planta Psidium (P.) guineense sw, popularmente conhecido como ‘Araçá Verdadeiro’, frente a células da cavidade oral. As células de mucosa oral dos doadores foram expostas ex-vivo ao extrato metanólico de Psidium guineense em concentrações (50, 100, 500 e 1000 µg/mL) por 30 minutos, houve a confecção de esfregaço do pellet de células e posterior fixação em lâminas coradas com Giemsa 2%. A análise foi feita com o uso de microscópio óptico, todo o experimento realizado em triplicata. Os dados revelam que mesmo em altas concentrações (500 e 1000 µg/mL) do extrato metanólico de P. guineense Sw. a toxicidade celular é considerada baixa com porcentagem de células normais (94,5% a 94%) compatíveis com o controle negativo. Logo, o extrato metanólico, pertencente a espécie P. guineense Sw. possui o potencial bioativo que pode ser explorado através de possível aplicação deste composto como fitoterápico, entretanto mais estudos devem ser realizados para melhor compreender o perfil de toxicidade deste produto.

This study aimed to analyze the typology of dairy production systems in Paraná State using management characteristics related to nutrition, milking, and technical aspects. We applied, in loco, 105 surveys in dairy production systems - DPS, located in Paraná State, Brazil. Variables related to farm structure, farmer social characteristics, and management practices applied in dairy systems, were collected. Exploratory Factor analysis (EFA) was used and resulted in three management factors, i.e., F1 (Nutrition Management), F2 (Technical Management), and F3 (Milking Management). Using factorial scores, cluster analysis was employed to identify homogeneous groups of dairy production systems. The dairy production systems in G2 (N=84 DPS) was characterized by prioritizing nutritional management (F1), which was the opposite result presented by G1 (N=21 DPS). The structural features and social characteristics of G1 and G2 were compared (T-test). The results indicated a great heterogeneity for the structural and productive characteristics of the analyzed dairy systems and socioeconomic characteristics of their managers. Results also indicate that producers with less structure and scale of production (Group 1), need more technical guidance in production system management. For producers with larger structures and scales of production (Group 2), continuous improvement investments are suggested in the three factors analyzed in this work - nutritional, technical, and milking. Such actions may maintain or increase the production and productivity results in these dairy systems. It is concluded that aspects related to nutritional management are the ones that mark the biggest difference between the cases analyzed, followed respectively by factors of technical management and milking management. Typology of dairy systems that adopt greater attention to nutritional management practices is characterized by a greater production structure and greater productivity when compared to a typology of dairy systems that prioritize actions of technical system management and milking management.

Changes in the in utero environment result in generational transfer of maladapted physiology in the context of conditions such as stress, obesity, and anxiety. Given the significant contribution of noncommunicable diseases—which are characterised by chronic inflammation—to population mortality, the potential for chronic maternal inflammation mediating foetal programming is a growing concern. The extent of generational transfer in terms of immune functionality and leukocyte glucocorticoid sensitivity was investigated over two generations of offspring (F1 and F2) in a model of chronic LPS-induced maternal inflammation in C57/BL/6 mice. Maternal inflammation resulted in glucocorticoid hypersensitivity (increased glucocorticoid receptor expression levels) in the majority of leukocyte subpopulations in both F1 and F2 offspring. Furthermore, splenocytes stimulated with LPS in vitro exhibited exacerbated inflammatory cytokine responses, which were even more prominent in F2 than F1; this effect could be ascribed to NLRP3 inflammasome hyperactivity in F1 but not F2. Current data illustrates that parental chronic inflammation may mediate the inflammatory profile in offspring, potentially propagating a maladapted proinflammatory phenotype in subsequent generations.

In this study, a method of numerical weather prediction by ensemble for the South American region is proposed. This method takes into account combinations of the numerical predictions of various models, assigning greater weight to models that exhibit the best performance. Nine operational numerical models were used to perform this study. The main objective of the study is to obtain a weather forecasting product (short-to-medium range) that combines what is best in each of the nine models used in the study, thus producing more reliable predictions. The proposed method was evaluated during austral summer (December 2012, and January and February 2013) and winter (June, July and August 2013). The results show that the proposed method can significantly improve the results provided by the numerical models and consequently has promising potential for operational applications in any weather forecasting center.

Hypothesizing that the Amazonian water system differences would affect the expression of muscle growth-related genes in juvenile tambaqui Colossoma macropomum (Cuvier 1818), this study aimed to analyze the morphometric data and expression of myogenic regulatory factors (MRFs) in the white and red muscle from tambaqui obtained from clear and black Amazonian water systems. All of the MRF transcript levels (myod, myf5, myogenin, and mrf4) were significantly lower in the red muscle from black water fish in comparison to clear water fish. However, in white muscle, only the myod transcript level was significantly decreased in the black water tambaqui. The changes in MRFs gene expression in muscle fibers of tambaqui from black water system provide relevant information about the environmental influence as that of water systems on gene expression of muscle growth related genes in the C. macropomum. Our results showed that the physical and chemical water characteristics change the expression of genes that promote muscle growth, and these results may be also widely applicable to future projects that aim to enhance muscle growth in fish that are of substantial interest to the aquaculture.