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Glucocorticoid-endocannabinoid interaction in cardiac surgical patients: relationship to early cognitive dysfunction and late depression

Background: Endocannabinoids (ECs) are rapidly acting immune-modulatory lipid-signaling molecules that are important for adaptation to stressful and aversive situations. They are known to interact with glucocorticoids and other stress-responsive systems. Maladaptation to acute or chronic stress represents a major risk factor for the development of psychiatric disorders. In the present study, we administered stress doses of hydrocortisone in a prospective, randomized, placebo-controlled double-blind study in patients undergoing cardiac surgery (CS) to examine the relationship between the use of glucocorticoids, plasma EC levels, and the occurrence of early postoperative cognitive dysfunction (delirium) and of later development of depression. Methods: We determined plasma levels of the ECs anandamide and 2-arachidonoylglycerol (2-AG) in CS patients of the hydrocortisone (n=56) and the placebo group (n=55) preoperatively, at postoperative day (POD) 1, at intensive care unit discharge, and at 6 months after CS (n=68). Postoperative delirium was diagnosed according to Diagnostic and Statistical Manual of the American Psychiatric Association IVth Edition (DSM-IV) criteria, and depression was determined by validated questionnaires and a standardized psychological interview (Structured Clinical Interview for DSM-IV). Results: Stress doses of hydrocortisone did not affect plasma EC levels and the occurrence of delirium or depression. However, patients who developed delirium on POD 1 had significantly lower preoperative 2-AG levels of the neuroprotective EC 2-AG (median values, 3.8 vs. 11.3 ng/ml; p=0.03). Preoperative 2-AG concentrations were predictive of postoperative delirium (sensitivity=0.70; specificity=0.69; cutoff value=4.9 ng/ml; receiver operating characteristic curve area=0.70; 95% confidence interval=0.54-0.85). Patients with depression at 6 months after CS (n=16) had significantly lower anandamide and 2-AG levels during the perioperative period. Conclusions: A low perioperative EC response may indicate an increased risk for early cognitive dysfunction and long-term depression in patients after CS. Glucocorticoids do not seem to influence this relationship

Dynamics of cytogenetic aberrations in Philadelphia chromosome positive and negative hematopoiesis during dasatinib therapy of chronic myeloid leukemia patients after imatinib failure

Clonal cytogenetic aberrations of the Philadelphia chromosome (Ph) positive hematopoiesis have been associated with the natural evolution of chronic myeloid leukemia (CML) to advanced disease. Clonal aberrations of Ph negative metaphases have been described after treatment with interferon or imatinib. This study evaluates the effect of dasatinib on Ph positive clones with additional cytogenetic aberrations and the frequency of novel aberrations in Ph positive and negative metaphases. Seventy-one patients treated with dasatinib after imatinib failure for a median of nine months were evaluated. Novel aberrations within Ph positive and negative clones appeared in six and three patients, respectively

Sensory analysis of cv. Fuyu persimmon fruits controlled atmosphere storage

[POR] O objetivo deste trabalho foi avaliar condições de armazenamento sobre a qualidade sensorial de caqui ‘Fuyu’. As condições de armazenamento foram: armazenamento refrigerado (AR); atmosfera controlada (AC) >10kPa O2 + 15kPa CO2; AC >10kPa O2 + 20kPa CO2; AC 0,5kPa O2 + 5kPa CO2; AC 0,5kPa O2 + 15kPa CO2, em delineamento inteiramente casualizado. As avaliações foram realizadas após três meses de armazenamento a –0,5°C seguido de três dias de exposição a 20°C. Na análise sensorial da cor, sabor e textura os provadores rejeitaram os frutos que permaneceram em AR, devido ao aspecto visual com escurecimento da epiderme. Com relação ao odor, os frutos que estavam na condição 0,5kPa O2 + 5kPa CO2 apresentaram maior aceitabilidade. Os provadores que preferem caqui firme consideraram frutos com melhor textura aqueles armazenados nas condições 0,5kPa O2 + 15kPa CO2; >10kPa O2 + 15 e 20kPa CO2 que apresentaram maior firmeza de polpa. Concluise que as condições de AC proporcionaram aos caquis ‘Fuyu’ melhores qualidades sensoriais que os frutos acondicionados em AR. As condições de AC avaliadas não diferiram entre si com relação às qualidades sensoriais. [ENG] The aim of this work was to evaluate the storage conditions on the sensory analysis of Fuyu persimmon fruits. The storage treatments were [1] cold storage (AR); [2] controlled atmosphere (CA) >10kPa O2 + 15kPa CO2; [3] (CA) >10kPa O2 + 20kPa CO2; [4] (CA) 0.5kPa O2 + 5kPa CO2; [5] (CA) 0.5kPa O2 + 15kPa CO2 using a randomised experimental design. The sensory evaluations were carried out after 3 months storange at –0.5°C plus 3 days at 20°C. For sensory analysis sky colour, flavour und texture were assessed. The sensory assessors rejected any fruit showing visual skin browning due to cold storage damage. Fruit stored in 0.5kPa O2 + 5kPa CO2 had the highest acceptability for flavour. The sensory assessor preferred persimmon fruit with a firm texture from either the 0.5kPa O2 + 15kPa CO2; >10kPa O2 + 15 e 20kPa CO2 storage treatments conditions, these treatments maintained the highest flesh firmness. CA conditions resulted in ‘Fuyu’ persimmon fruit with better sensorial qualities that fruit stored in coold storage. The CA stored conditions did not differ significantly with respect to the sensorial qualities.À Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS) e Brasilien-Zentrum pelo fomento e possibilidade da realização do intercâmbio internacional (doutorado-sanduíche) do primeiro autor e ao Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) pela concessão de bolsas de estudo ao primeiro autor nos estudos realizados no Brasil. À Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) pela concessão de bolsa ao quarto autor

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

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

Parâmetros termodinâmicos da interação de (R) tetracarboxilatos de Rh (II) com uma tiol-enzima

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