Universidade Federal de Minas Gerais

About: Universidade Federal de Minas Gerais is a education organization based out in Belo Horizonte, Minas Gerais, Brazil. It is known for research contribution in the topics: Population & Context (language use). The organization has 41631 authors who have published 75688 publications receiving 1249905 citations.

Medicinal plants and other botanical products from the Brazilian Official Pharmacopoeia

Abstract: In this paper, we describe the results of a thorough survey in the four editions of the Brazilian Official Pharmacopoeia (FBRAS), in a search for data about the plants and other botanical products included in them. The growth of the pharmaceutical industry since the second half of last century markedly affected the Brazilian official medicine. The paper analyses the transformation within the Pharmacopoeia, focusing on the presence of Monographs for Native medicinal plants. The result showed a strong substitution of Native American medicinal plants by industrialized medicine and foreign medicinal plants in FBRAS and confirms the necessity of investiments in research for the validation of Brazilian Native plants.

From bias to opinion: a transfer-learning approach to real-time sentiment analysis

Abstract: Real-time interaction, which enables live discussions, has become a key feature of most Web applications. In such an environment, the ability to automatically analyze user opinions and sentiments as discussions develop is a powerful resource known as real time sentiment analysis. However, this task comes with several challenges, including the need to deal with highly dynamic textual content that is characterized by changes in vocabulary and its subjective meaning and the lack of labeled data needed to support supervised classifiers. In this paper, we propose a transfer learning strategy to perform real time sentiment analysis. We identify a task - opinion holder bias prediction - which is strongly related to the sentiment analysis task; however, in constrast to sentiment analysis, it builds accurate models since the underlying relational data follows a stationary distribution.Instead of learning textual models to predict content polarity (i.e., the traditional sentiment analysis approach), we first measure the bias of social media users toward a topic, by solving a relational learning task over a network of users connected by endorsements (e.g., retweets in Twitter). We then analyze sentiments by transferring user biases to textual features. This approach works because while new terms may arise and old terms may change their meaning, user bias tends to be more consistent over time as a basic property of human behavior. Thus, we adopted user bias as the basis for building accurate classification models. We applied our model to posts collected from Twitter on two topics: the 2010 Brazilian Presidential Elections and the 2010 season of Brazilian Soccer League. Our results show that knowing the bias of only 10% of users generates an F1 accuracy level ranging from 80% to 90% in predicting user sentiment in tweets.

Charge-Transfer Mechanism in Graphene-Enhanced Raman Scattering

Abstract: In the chemical enhancement mechanism for Raman scattering, the two types of charge-transfer models, the excited-state and the ground-state charge-transfer mechanisms, present the different depende...

Bandoniozyma gen. nov., a Genus of Fermentative and Non-Fermentative Tremellaceous Yeast Species

Abstract: Background: Independent surveys across the globe led to the proposal of a new basidiomycetous yeast genus within the Bulleromyces clade of the Tremellales, Bandoniozyma gen. nov., with seven new species. Methodology/Principal Findings: The species were characterized by multiple methods, including the analysis of D1/D2 and ITS nucleotide sequences, and morphological and physiological/biochemical traits. Most species can ferment glucose, which is an unusual trait among basidiomycetous yeasts. Conclusions/Significance: In this study we propose the new yeast genus Bandoniozyma, with seven species Bandoniozyma noutii sp. nov. (type species of genus; CBS 8364 T = DBVPG 4489 T ), Bandoniozyma aquatica sp. nov. (UFMG-DH4.20 T = CBS 12527 T = ATCC MYA-4876 T ), Bandoniozyma complexa sp. nov. (CBS 11570 T = ATCC MYA-4603 T = MA28a T ), Bandoniozyma fermentans sp. nov. (CBS 12399 T = NU7M71 T = BCRC 23267 T ), Bandoniozyma glucofermentans sp. nov. (CBS 10381 T = NRRL Y-48076 T = ATCC MYA-4760 T = BG 02-7-15-015A-1-1 T ), Bandoniozyma tunnelae sp. nov. (CBS 8024 T = DBVPG 7000 T ), and Bandoniozyma visegradensis sp. nov. (CBS 12505 T = NRRL Y-48783 T = NCAIM Y.01952 T ).

Effect of procalcitonin-guided antibiotic treatment on clinical outcomes in intensive care unit patients with infection and sepsis patients : a patient-level meta-analysis of randomized trials

Abstract: The clinical utility of serum procalcitonin levels in guiding antibiotic treatment decisions in patients with sepsis remains unclear. This patient-level meta-analysis based on 11 randomized trials investigates the impact of procalcitonin-guided antibiotic therapy on mortality in intensive care unit (ICU) patients with infection, both overall and stratified according to sepsis definition, severity, and type of infection. For this meta-analysis focusing on procalcitonin-guided antibiotic management in critically ill patients with sepsis of any type, in February 2018 we updated the database of a previous individual patient data meta-analysis which was limited to patients with respiratory infections only. We used individual patient data from 11 trials that randomly assigned patients to receive antibiotics based on procalcitonin levels (the “procalcitonin-guided” group) or the current standard of care (the “controls”). The primary endpoint was mortality within 30 days. Secondary endpoints were duration of antibiotic treatment and length of stay. Mortality in the 2252 procalcitonin-guided patients was significantly lower compared with the 2230 control group patients (21.1% vs 23.7%; adjusted odds ratio 0.89, 95% confidence interval (CI) 0.8 to 0.99; p = 0.03). These effects on mortality persisted in a subgroup of patients meeting the sepsis 3 definition and based on the severity of sepsis (assessed on the basis of the Sequential Organ Failure Assessment (SOFA) score, occurrence of septic shock or renal failure, and need for vasopressor or ventilatory support) and on the type of infection (respiratory, urinary tract, abdominal, skin, or central nervous system), with interaction for each analysis being > 0.05. Procalcitonin guidance also facilitated earlier discontinuation of antibiotics, with a reduction in treatment duration (9.3 vs 10.4 days; adjusted coefficient −1.19 days, 95% CI −1.73 to −0.66; p < 0.001). Procalcitonin-guided antibiotic treatment in ICU patients with infection and sepsis patients results in improved survival and lower antibiotic treatment duration.