Resposta do cafeeiro conilon à adubação de npk em sistema de plantio adensado

The response of plants to the application of fertilizer varies in function of diverse factors, among them we highlight the type of soil, dose of nutrient, and spacing used. Thus, the objective of this work was to evaluate the effect of NPK application in the production of Conilon coffee plants (Coffea canephora Pierre ex Forehn.), cultivated in different densities of planting. The studied were composed of four quantities of N (0, 150, 300 and 450 kg ha-1), four of P2O5 (0, 50, 100 and 150 kg ha-1), four of K2O (0, 150, 300 and 450 kg ha-1) and four densities of planting: 2,0 x 1,0 (5000 plants ha-1); 2,5 x 1,0 (4000 plants ha-1); 3,0 x 1,0 (3000 plants ha-1) and 3,0 x 1,5 m (2222 plants ha-1). It was used the experimental design in randomized blocks, being the treatment distributed in four blocks arranged in a factorial fractional (4 x 4 x 4)1/2 scheme. There was a reduction in the dose of nitrogen in relation to those normally recommended for the Conilon coffee plants. The potassium did not influence the production. The phosphorus increased the productivity; however, it was not possible to determinate the maximum economic dose. There were no interactions between the densities of planting and the level of NPK applied. As respostas das plantas à aplicação de fertilizantes variam em função de vários fatores, dentre os quais se destacam o tipo de solo, doses dos nutrientes e o espaçamento utilizado. O objetivo deste trabalho foi avaliar o efeito da adubação de nitrogênio, fósforo e potássio (NPK) na produção do cafeeiro Conilon (Coffea canephora Pierre ex Froehn.), cultivado em diferentes densidades de plantio. Foram utilizadas quatro doses de N (0, 150, 300 e 450 kg ha-1), quatro de P2O5 (0, 50, 100 e 150 kg ha-1), quatro de K2O (0, 150, 300 e 450 kg ha-1) e quatro densidades de plantio: 2,0 x 1,0 (5.000 plantas ha-1); 2,5 x 1,0 (4.000 plantas ha-1); 3,0 x 1,0 (3.000 plantas ha-1) e 3,0 x 1,5 m (2.222 plantas ha-1). Foi utilizado o delineamento experimental em blocos casualizados, sendo os tratamentos distribuídos em quatro blocos arranjados em um esquema de fatorial fracionado (4 x 4 x 4)1/2. Houve uma redução na dose de N em relação às doses normalmente recomendadas para o cafeeiro Conilon. O K não influenciou a produtividade. O P aumentou a produtividade, entretanto, não foi possível determinar a dose máxima econômica. Não houve interações entre as densidades de plantio e os níveis de NPK avaliados.

In vitro functional models for human liver diseases and drug screening: beyond animal testing

Liver is one of the most important and complex organs in the human body, being characterized by a sophisticated microarchitecture and responsible for key physiological functions. Despite its remarkable ability to regenerate, acute liver failure and chronic liver diseases are major causes of morbidity and mortality worldwide. Therefore, understanding the molecular mechanisms underlying such liver disorders is critical for the successful development of novel therapeutics. In this frame, preclinical animal models have been portrayed as the most commonly used tool to address such issues. However, due to significant species differences in liver architecture, regenerative capacity, disease progression, inflammatory markers, metabolism rates, and drug response, animal models cannot fully recapitulate the complexity of human liver metabolism. As a result, translational research to model human liver diseases and drug screening platforms may yield limited results, leading to failure scenarios. To overcome this impasse, over the last decade, 3D human liver in vitro models have been proposed as an alternative to pre-clinical animal models. These systems have been successfully employed for the investigation of the etiology and dynamics of liver diseases, for drug screening, and - more recently - to design patient-tailored therapies, resulting in potentially higher efficacy and reduced costs compared to other methods. Here, we review the most recent advances in this rapidly evolving field with particular attention to organoid cultures, liver-on-a-chip platforms, and engineered scaffold-based approaches

In silico analysis and theratyping of an ultra-rare CFTR genotype (W57G/A234D) in primary human rectal and nasal epithelial cells

Mutation targeted therapy in cystic fibrosis (CF) is still not eligible for all CF subjects, especially for cases carrying rare variants such as the CFTR genotype W57G/A234D (c.169T>G/c.701C>A). We performed in silico analysis of the effects of these variants on protein stability, which we functionally characterized using colonoids and reprogrammed nasal epithelial cells. The effect of mutations on cystic fibrosis transmembrane conductance regulator (CFTR) protein was analyzed by western blotting, forskolin-induced swelling (FIS), and Ussing chamber analysis. We detected a residual CFTR function that increases following treatment with the CFTR modulators VX661±VX445±VX770, correlates among models, and is associated with increased CFTR protein levels following treatment with CFTR correctors. In vivo treatment with VX770 reduced sweat chloride concentration to non-CF levels, increased the number of CFTR-dependent sweat droplets, and induced a 6% absolute increase in predicted FEV1% after 27 weeks of treatment indicating the relevance of theratyping with patient-derived cells in CF

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90ĝ€¯d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and "hotspots"of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Type I interferon-mediated autoinflammation due to DNase II deficiency

Microbial nucleic acid recognition serves as the major stimulus to an antiviral response, implying a requirement to limit the misrepresentation of self nucleic acids as non-self and the induction of autoinflammation. By systematic screening using a panel of interferon-stimulated genes we identify two siblings and a singleton variably demonstrating severe neonatal anemia, membranoproliferative glomerulonephritis, liver fibrosis, deforming arthropathy and increased anti-DNA antibodies. In both families we identify biallelic mutations in DNASE2, associated with a loss of DNase II endonuclease activity. We record increased interferon alpha protein levels using digital ELISA, enhanced interferon signaling by RNA-Seq analysis and constitutive upregulation of phosphorylated STAT1 and STAT3 in patient lymphocytes and monocytes. A hematological disease transcriptomic signature and increased numbers of erythroblasts are recorded in patient peripheral blood, suggesting that interferon might have a particular effect on hematopoiesis. These data define a type I interferonopathy due to DNase II deficiency in humans