Showing papers by "Universidade Federal de Minas Gerais published in 2019"

SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python

Abstract: SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments.

GLIM Criteria for the Diagnosis of Malnutrition: A Consensus Report From the Global Clinical Nutrition Community

Abstract: Summary Rationale This initiative is focused on building a global consensus around core diagnostic criteria for malnutrition in adults in clinical settings Methods In January 2016, the Global Leadership Initiative on Malnutrition (GLIM) was convened by several of the major global clinical nutrition societies GLIM appointed a core leadership committee and a supporting working group with representatives bringing additional global diversity and expertise Empirical consensus was reached through a series of face-to-face meetings, telephone conferences, and e-mail communications Results A two-step approach for the malnutrition diagnosis was selected, ie, first screening to identify “at risk” status by the use of any validated screening tool, and second, assessment for diagnosis and grading the severity of malnutrition The malnutrition criteria for consideration were retrieved from existing approaches for screening and assessment Potential criteria were subjected to a ballot among the GLIM core and supporting working group members The top five ranked criteria included three phenotypic criteria (non-volitional weight loss, low body mass index, and reduced muscle mass) and two etiologic criteria (reduced food intake or assimilation, and inflammation or disease burden) To diagnose malnutrition at least one phenotypic criterion and one etiologic criterion should be present Phenotypic metrics for grading severity as Stage 1 (moderate) and Stage 2 (severe) malnutrition are proposed It is recommended that the etiologic criteria be used to guide intervention and anticipated outcomes The recommended approach supports classification of malnutrition into four etiology-related diagnosis categories Conclusion A consensus scheme for diagnosing malnutrition in adults in clinical settings on a global scale is proposed Next steps are to secure further collaboration and endorsements from leading nutrition professional societies, to identify overlaps with syndromes like cachexia and sarcopenia, and to promote dissemination, validation studies, and feedback The diagnostic construct should be re-considered every 3–5 years

GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.

Abstract: Rationale This initiative is focused on building a global consensus around core diagnostic criteria for malnutrition in adults in clinical settings.

Global, regional, and national burden of suicide mortality 1990 to 2016: systematic analysis for the Global Burden of Disease Study 2016

Abstract: Objectives To use the estimates from the Global Burden of Disease Study 2016 to describe patterns of suicide mortality globally, regionally, and for 195 countries and territories by age, sex, and Socio-demographic index, and to describe temporal trends between 1990 and 2016. Design Systematic analysis. Main outcome measures Crude and age standardised rates from suicide mortality and years of life lost were compared across regions and countries, and by age, sex, and Socio-demographic index (a composite measure of fertility, income, and education). Results The total number of deaths from suicide increased by 6.7% (95% uncertainty interval 0.4% to 15.6%) globally over the 27 year study period to 817 000 (762 000 to 884 000) deaths in 2016. However, the age standardised mortality rate for suicide decreased by 32.7% (27.2% to 36.6%) worldwide between 1990 and 2016, similar to the decline in the global age standardised mortality rate of 30.6%. Suicide was the leading cause of age standardised years of life lost in the Global Burden of Disease region of high income Asia Pacific and was among the top 10 leading causes in eastern Europe, central Europe, western Europe, central Asia, Australasia, southern Latin America, and high income North America. Rates for men were higher than for women across regions, countries, and age groups, except for the 15 to 19 age group. There was variation in the female to male ratio, with higher ratios at lower levels of Socio-demographic index. Women experienced greater decreases in mortality rates (49.0%, 95% uncertainty interval 42.6% to 54.6%) than men (23.8%, 15.6% to 32.7%). Conclusions Age standardised mortality rates for suicide have greatly reduced since 1990, but suicide remains an important contributor to mortality worldwide. Suicide mortality was variable across locations, between sexes, and between age groups. Suicide prevention strategies can be targeted towards vulnerable populations if they are informed by variations in mortality rates.

Supervised Learning for Fake News Detection

Abstract: A large body of recent works has focused on understanding and detecting fake news stories that are disseminated on social media. To accomplish this goal, these works explore several types of features extracted from news stories, including source and posts from social media. In addition to exploring the main features proposed in the literature for fake news detection, we present a new set of features and measure the prediction performance of current approaches and features for automatic detection of fake news. Our results reveal interesting findings on the usefulness and importance of features for detecting false news. Finally, we discuss how fake news detection approaches can be used in the practice, highlighting challenges and opportunities.

Association between consumption of ultra-processed foods and all cause mortality: SUN prospective cohort study.

Abstract: Objective To evaluate the association between consumption of ultra-processed foods and all cause mortality. Design Prospective cohort study. Setting Seguimiento Universidad de Navarra (SUN) cohort of university graduates, Spain 1999-2018. Participants 19 899 participants (12 113 women and 7786 men) aged 20-91 years followed-up every two years between December 1999 and February 2014 for food and drink consumption, classified according to the degree of processing by the NOVA classification, and evaluated through a validated 136 item food frequency questionnaire. Main outcome measure Association between consumption of energy adjusted ultra-processed foods categorised into quarters (low, low-medium, medium-high, and high consumption) and all cause mortality, using multivariable Cox proportional hazard models. Results 335 deaths occurred during 200 432 persons years of follow-up. Participants in the highest quarter (high consumption) of ultra-processed foods consumption had a higher hazard for all cause mortality compared with those in the lowest quarter (multivariable adjusted hazard ratio 1.62, 95% confidence interval 1.13 to 2.33) with a significant dose-response relation (P for linear trend=0.005). For each additional serving of ultra-processed foods, all cause mortality relatively increased by 18% (adjusted hazard ratio 1.18, 95% confidence interval 1.05 to 1.33). Conclusions A higher consumption of ultra-processed foods (>4 servings daily) was independently associated with a 62% relatively increased hazard for all cause mortality. For each additional serving of ultra-processed food, all cause mortality increased by 18%. Study registration ClinicalTrials.gov NCT02669602.

Visible Light Communication: Concepts, Applications and Challenges

Abstract: During the last decade, the exponential growth of mobile devices and wireless services created a huge demand for radio frequency-based technologies. Meanwhile, the lighting industry has been revolutionized due to the popularization of LED light bulbs, which are more economical and efficient. In that context, visible light communication (VLC) is a disruptive technology based on LEDs that offers a free spectrum and high data rate, which can potentially serve as a complementary technology to the current radio frequency standards. In this paper, we present a comprehensive state-of-the-art survey of VLC, as well as the main concepts and challenges related to this emergent area. We overview VLC technology, from its physical aspects and communication architecture to its main applications and research challenges. Finally, we present the main research platforms available today, along with a deep analysis of the system design and future directions in the field.

Alzheimer's disease: risk factors and potentially protective measures.

Abstract: Alzheimer’s disease (AD) is the most common type of dementia and typically manifests through a progressive loss of episodic memory and cognitive function, subsequently causing language and visuospatial skills deficiencies, which are often accompanied by behavioral disorders such as apathy, aggressiveness and depression. The presence of extracellular plaques of insoluble β-amyloid peptide (Aβ) and neurofibrillary tangles (NFT) containing hyperphosphorylated tau protein (P-tau) in the neuronal cytoplasm is a remarkable pathophysiological cause in patients’ brains. Approximately 70% of the risk of developing AD can be attributed to genetics. However, acquired factors such as cerebrovascular diseases, diabetes, hypertension, obesity and dyslipidemia increase the risk of AD development. The aim of the present minireview was to summarize the pathophysiological mechanism and the main risk factors for AD. As a complement, some protective factors associated with a lower risk of disease incidence, such as cognitive reserve, physical activity and diet will also be addressed.

Fresh versus elective frozen embryo transfer in IVF/ICSI cycles: a systematic review and meta-analysis of reproductive outcomes.

Abstract: Background Elective freezing of all good quality embryos and transfer in subsequent cycles, i.e. elective frozen embryo transfer (eFET), has recently increased significantly with the introduction of the GnRH agonist trigger protocol and improvements in cryo-techniques. The ongoing discussion focuses on whether eFET should be offered to the overall IVF population or only to specific subsets of patients. Until recently, the clinical usage of eFET was supported by only a few randomized controlled trials (RCT) and meta-analyses, suggesting that the eFET not only reduced ovarian hyperstimulation syndrome (OHSS), but also improved reproductive outcomes. However, the evidence is not unequivocal, and recent RCTs challenge the use of eFET for the general IVF population. Objective and rationale This systematic review and meta-analysis aimed at evaluating whether eFET is advantageous for reproductive, obstetric and perinatal outcomes compared with fresh embryo transfer in IVF/ICSI cycles. Additionally, we evaluated the effectiveness of eFET in comparison to fresh embryo transfer in different subgroups of patients undergoing IVF/ICSI cycles. Search methods We conducted a systematic review, using PubMed/Medline and EMBASE to identify all relevant RCTs published until March 2018. The participants included infertile couples undergoing IVF/ICSI with or without preimplantation genetic testing for aneuploidy (PGT-A). The primary outcome was the live birth rate (LBR), whereas secondary outcomes were cumulative LBR, implantation rate, miscarriage, OHSS, ectopic pregnancy, preterm birth, pregnancy-induced hypertension, pre-eclampsia, mean birthweight and congenital anomalies. Subgroup analyses included normal and hyper-responder patients, embryo developmental stage on the day of embryo transfer, freezing method and the route of progesterone administration for luteal phase support in eFET cycles. Outcomes Eleven studies, including 5379 patients, fulfilling the inclusion criteria were subjected to qualitative and quantitative analysis. A significant increase in LBR was noted with eFET compared with fresh embryo transfer in the overall IVF/ICSI population [risk ratio (RR) = 1.12; 95% CI: 1.01-1.24]. Subgroup analyses indicated higher LBRs by eFET than by fresh embryo transfer in hyper-responders (RR = 1.16; 95% CI: 1.05-1.28) and in PGT-A cycles (RR = 1.55; 95% CI: 1.14-2.10). However, no differences were observed for LBR in normo-responders (RR = 1.03; 95% CI: 0.91-1.17); moreover, the cumulative LBR was not significantly different in the overall population (RR = 1.04; 95% CI: 0.97-1.11). Regarding safety, the risk of moderate/severe OHSS was significantly lower with eFET than with fresh embryo transfer (RR = 0.42; 95% CI: 0.19-0.96). In contrast, the risk of pre-eclampsia increased with eFET (RR = 1.79; 95% CI: 1.03-3.09). No statistical differences were noted in the remaining secondary outcomes. Wider implications Although the use of eFET has steadily increased in recent years, a significant increase in LBR with eFET was solely noted in hyper-responders and in patients undergoing PGT-A. Concerning safety, eFET significantly decreases the risk of moderate and severe OHSS, albeit at the expense of an increased risk of pre-eclampsia.

Detecting gravitational waves from cosmological phase transitions with LISA: an update

Abstract: We investigate the potential for observing gravitational waves from cosmological phase transitions with LISA in light of recent theoretical and experimental developments. Our analysis is based on current state-of-the-art simulations of sound waves in the cosmic fluid after the phase transition completes. We discuss the various sources of gravitational radiation, the underlying parameters describing the phase transition and a variety of viable particle physics models in this context, clarifying common misconceptions that appear in the literature and identifying open questions requiring future study. We also present a web-based tool, PTPlot, that allows users to obtain up-to-date detection prospects for a given set of phase transition parameters at LISA.

Biodiversity recovery of Neotropical secondary forests

Abstract: Old-growth tropical forests harbor an immense diversity of tree species but are rapidly being cleared, while secondary forests that regrow on abandoned agricultural lands increase in extent. We assess how tree species richness and composition recover during secondary succession across gradients in environmental conditions and anthropogenic disturbance in an unprecedented multisite analysis for the Neotropics. Secondary forests recover remarkably fast in species richness but slowly in species composition. Secondary forests take a median time of five decades to recover the species richness of old-growth forest (80% recovery after 20 years) based on rarefaction analysis. Full recovery of species composition takes centuries (only 34% recovery after 20 years). A dual strategy that maintains both old-growth forests and species-rich secondary forests is therefore crucial for biodiversity conservation in human-modified tropical landscapes.

Lipopolysaccharide-Induced Neuroinflammation as a Bridge to Understand Neurodegeneration.

Abstract: A large body of experimental evidence suggests that neuroinflammation is a key pathological event triggering and perpetuating the neurodegenerative process associated with many neurological diseases. Therefore, different stimuli, such as lipopolysaccharide (LPS), are used to model neuroinflammation associated with neurodegeneration. By acting at its receptors, LPS activates various intracellular molecules, which alter the expression of a plethora of inflammatory mediators. These factors, in turn, initiate or contribute to the development of neurodegenerative processes. Therefore, LPS is an important tool for the study of neuroinflammation associated with neurodegenerative diseases. However, the serotype, route of administration, and number of injections of this toxin induce varied pathological responses. Thus, here, we review the use of LPS in various models of neurodegeneration as well as discuss the neuroinflammatory mechanisms induced by this toxin that could underpin the pathological events linked to the neurodegenerative process.

Automatic diagnosis of the 12-lead ECG using a deep neural network

Abstract: The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice.

Genome Detective: an automated system for virus identification from high-throughput sequencing data.

Abstract: SUMMARY Genome Detective is an easy to use web-based software application that assembles the genomes of viruses quickly and accurately. The application uses a novel alignment method that constructs genomes by reference-based linking of de novo contigs by combining amino-acids and nucleotide scores. The software was optimized using synthetic datasets to represent the great diversity of virus genomes. The application was then validated with next generation sequencing data of hundreds of viruses. User time is minimal and it is limited to the time required to upload the data. AVAILABILITY AND IMPLEMENTATION Available online: http://www.genomedetective.com/app/typingtool/virus/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Comment on “The global tree restoration potential”

Abstract: Bastin et al.’s estimate (Reports, 5 July 2019, p. 76) that tree planting for climate change mitigation could sequester 205 gigatonnes of carbon is approximately five times too large. Their analysis inflated soil organic carbon gains, failed to safeguard against warming from trees at high latitudes and elevations, and considered afforestation of savannas, grasslands, and shrublands to be restoration.

Microbiota-derived acetate protects against respiratory syncytial virus infection through a GPR43-type 1 interferon response

Abstract: Severe respiratory syncytial virus (RSV) infection is a major cause of morbidity and mortality in infants <2 years-old. Here we describe that high-fiber diet protects mice from RSV infection. This effect was dependent on intestinal microbiota and production of acetate. Oral administration of acetate mediated interferon-β (IFN-β) response by increasing expression of interferon-stimulated genes in the lung. These effects were associated with reduction of viral load and pulmonary inflammation in RSV-infected mice. Type 1 IFN signaling via the IFN-1 receptor (IFNAR) was essential for acetate antiviral activity in pulmonary epithelial cell lines and for the acetate protective effect in RSV-infected mice. Activation of Gpr43 in pulmonary epithelial cells reduced virus-induced cytotoxicity and promoted antiviral effects through IFN-β response. The effect of acetate on RSV infection was abolished in Gpr43−/− mice. Our findings reveal antiviral effects of acetate involving IFN-β in lung epithelial cells and engagement of GPR43 and IFNAR. Dietary fibers and SCFAs can exert a protective effect against respiratory syncytial virus (RSV). Here, the authors report that microbiota-derived acetate protects mice against RSV infection via GPR43- mediated type 1 interferon response induction in the lungs.

Compartmentalized gut lymph node drainage dictates adaptive immune responses

Abstract: The intestinal immune system has the challenging task of tolerating foreign nutrients and the commensal microbiome, while excluding or eliminating ingested pathogens. Failure of this balance leads to conditions such as inflammatory bowel diseases, food allergies and invasive gastrointestinal infections1. Multiple immune mechanisms are therefore in place to maintain tissue integrity, including balanced generation of effector T (TH) cells and FOXP3+ regulatory T (pTreg) cells, which mediate resistance to pathogens and regulate excessive immune activation, respectively1–4. The gut-draining lymph nodes (gLNs) are key sites for orchestrating adaptive immunity to luminal perturbations5–7. However, it is unclear how they simultaneously support tolerogenic and inflammatory reactions. Here we show that gLNs are immunologically specific to the functional gut segment that they drain. Stromal and dendritic cell gene signatures and polarization of T cells against the same luminal antigen differ between gLNs, with the proximal small intestine-draining gLNs preferentially giving rise to tolerogenic responses and the distal gLNs to pro-inflammatory T cell responses. This segregation permitted the targeting of distal gLNs for vaccination and the maintenance of duodenal pTreg cell induction during colonic infection. Conversely, the compartmentalized dichotomy was perturbed by surgical removal of select distal gLNs and duodenal infection, with effects on both lymphoid organ and tissue immune responses. Our findings reveal that the conflict between tolerogenic and inflammatory intestinal responses is in part resolved by discrete gLN drainage, and encourage antigen targeting to specific gut segments for therapeutic immune modulation. Immune responses in the gut and associated draining lymph nodes differ between tolerogenic and inflammatory depending on their anatomical location.

Occurrence, fate and removal of pharmaceutically active compounds (PhACs) in water and wastewater treatment plants—A review

Abstract: This paper reviews the occurrence of Pharmaceutically active compounds (PhACs) in water and wastewater worldwide as well as their fate, focusing on the removal by conventional water and wastewater treatment plants and the risk imposed to human health associated to the presence of PhACs in raw and drinking water. For this, it was assessed 23 drinking water treatment plants and 30 municipal wastewater treatment plants around the world of different capacities. Due to the high stability, intrinsic characteristics and low concentration, adsorption to the sludge and biodegradation are the most used path to remove of these compounds in wastewater treatment plants (WWTP). In water treatment plants (WTP), chlorination and application of activated granular carbon are the processes associated with the highest removal of pharmaceutical compounds, but, in general, conventional WTPs are able to reduce but not completely remove PhACs in potable water. Carbamazepine, gemfizobril and fenofibrate are found to be the PhACs that risks to human health could not be excluded. This indicates the necessity of investments in advanced techniques for the treatment of water and wastewater. The results also point to the need for more studies focusing on the determination of guideline values for drinking water of more PhACs.

Fuzzy Control Systems: Past, Present and Future

Abstract: More than 40 years after fuzzy logic control appeared as an effective tool to deal with complex processes, the research on fuzzy control systems has constantly evolved. Mamdani fuzzy control was originally introduced as a modelfree control approach based on expert?s experience and knowledge. Due to the lack of a systematic framework to study Mamdani fuzzy systems, we have witnessed growing interest in fuzzy model-based approaches with Takagi-Sugeno fuzzy systems and singleton-type fuzzy systems (also called piecewise multiaffine systems) over the past decades. This paper reviews the key features of the three above types of fuzzy systems. Through these features, we point out the historical rationale for each type of fuzzy systems and its current research mainstreams. However, the focus is put on fuzzy model-based approaches developed via Lyapunov stability theorem and linear matrix inequality (LMI) formulations. Finally, our personal viewpoint on the perspectives and challenges of the future fuzzy control research is discussed.

A research agenda for seed-trait functional ecology.

Abstract: Trait-based approaches have improved our understanding of plant evolution, community assembly and ecosystem functioning. A major challenge for the upcoming decades is to understand the functions and evolution of early life-history traits, across levels of organization and ecological strategies. Although a variety of seed traits are critical for dispersal, persistence, germination timing and seedling establishment, only seed mass has been considered systematically. Here we suggest broadening the range of morphological, physiological and biochemical seed traits to add new understanding on plant niches, population dynamics and community assembly. The diversity of seed traits and functions provides an important challenge that will require international collaboration in three areas of research. First, we present a conceptual framework for a seed ecological spectrum that builds upon current understanding of plant niches. We then lay the foundation for a seed-trait functional network, the establishment of which will underpin and facilitate trait-based inferences. Finally, we anticipate novel insights and challenges associated with incorporating diverse seed traits into predictive evolutionary ecology, community ecology and applied ecology. If the community invests in standardized seed-trait collection and the implementation of rigorous databases, major strides can be made at this exciting frontier of functional ecology.

Resilience and restoration of tropical and subtropical grasslands, savannas, and grassy woodlands.

Abstract: Despite growing recognition of the conservation values of grassy biomes, our understanding of how to maintain and restore biodiverse tropical grasslands (including savannas and open-canopy grassy woodlands) remains limited. To incorporate grasslands into large-scale restoration efforts, we synthesised existing ecological knowledge of tropical grassland resilience and approaches to plant community restoration. Tropical grassland plant communities are resilient to, and often dependent on, the endogenous disturbances with which they evolved - frequent fires and native megafaunal herbivory. In stark contrast, tropical grasslands are extremely vulnerable to human-caused exogenous disturbances, particularly those that alter soils and destroy belowground biomass (e.g. tillage agriculture, surface mining); tropical grassland restoration after severe soil disturbances is expensive and rarely achieves management targets. Where grasslands have been degraded by altered disturbance regimes (e.g. fire exclusion), exotic plant invasions, or afforestation, restoration efforts can recreate vegetation structure (i.e. historical tree density and herbaceous ground cover), but species-diverse plant communities, including endemic species, are slow to recover. Complicating plant-community restoration efforts, many tropical grassland species, particularly those that invest in underground storage organs, are difficult to propagate and re-establish. To guide restoration decisions, we draw on the old-growth grassland concept, the novel ecosystem concept, and theory regarding tree cover along resource gradients in savannas to propose a conceptual framework that classifies tropical grasslands into three broad ecosystem states. These states are: (1) old-growth grasslands (i.e. ancient, biodiverse grassy ecosystems), where management should focus on the maintenance of disturbance regimes; (2) hybrid grasslands, where restoration should emphasise a return towards the old-growth state; and (3) novel ecosystems, where the magnitude of environmental change (i.e. a shift to an alternative ecosystem state) or the socioecological context preclude a return to historical conditions.

Strategic approaches to restoring ecosystems can triple conservation gains and halve costs

Abstract: International commitments for ecosystem restoration add up to one-quarter of the world’s arable land. Fulfilling them would ease global challenges such as climate change and biodiversity decline but could displace food production and impose financial costs on farmers. Here, we present a restoration prioritization approach capable of revealing these synergies and trade-offs, incorporating ecological and economic efficiencies of scale and modelling specific policy options. Using an actual large-scale restoration target of the Atlantic Forest hotspot, we show that our approach can deliver an eightfold increase in cost-effectiveness for biodiversity conservation compared with a baseline of non-systematic restoration. A compromise solution avoids 26% of the biome’s current extinction debt of 2,864 plant and animal species (an increase of 257% compared with the baseline). Moreover, this solution sequesters 1 billion tonnes of CO2-equivalent (a 105% increase) while reducing costs by US$28 billion (a 57% decrease). Seizing similar opportunities elsewhere would offer substantial contributions to some of the greatest challenges for humankind. A restoration prioritization approach applied to the Brazilian Atlantic Forest biodiversity hotspot considers 362 scenarios for synergies and trade-offs between ecological and economic costs, benefits and scales.

The Oral Microbiota Is Modified by Systemic Diseases.

Abstract: Periodontal diseases are initiated by bacteria that accumulate in a biofilm on the tooth surface and affect the adjacent periodontal tissue. Systemic diseases such as diabetes, rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE) increase susceptibility to destructive periodontal diseases. In human studies and in animal models, these diseases have been shown to enhance inflammation in the periodontium and increase the risk or severity of periodontitis. All 3 systemic diseases are linked to a decrease in bacterial taxa associated with health and an increase in taxa associated with disease. Although there is controversy regarding the specific oral bacterial changes associated with each disease, it has been reported that diabetes increases the levels of Capnocytophaga, Porphyromonas, and Pseudomonas, while Prevotella and Selenomonas are increased in RA and Selenomonas, Leptotrichia, and Prevotella in SLE. In an animal model, diabetes increased the pathogenicity of the oral microbiome, as shown by increased inflammation, osteoclastogenesis, and periodontal bone loss when transferred to normal germ-free hosts. Moreover, in diabetic animals, the increased pathogenicity could be substantially reversed by inhibition of IL-17, indicating that host inflammation altered the microbial pathogenicity. Increased IL-17 has also been shown in SLE, RA, and leukocyte adhesion deficiency and may contribute to oral microbial changes in these diseases. Successful RA treatment with anti-inflammatory drugs partially reverses the oral microbial dysbiosis. Together, these data demonstrate that systemic diseases characterized by enhanced inflammation disturb the oral microbiota and point to IL-17 as key mediator in this process.

Fighting Pathogenic Bacteria on Two Fronts: Phages and Antibiotics as Combined Strategy.

Abstract: With the emerging threat of infections caused by multidrug resistant bacteria, phages have been reconsidered as an alternative for treating infections caused by tenacious pathogens. However, instead of replacing antibiotics, the combination of both types of antimicrobials can be superior over the use of single agents. Enhanced bacterial suppression, more efficient penetration into biofilms, and lowered chances for the emergence of phage resistance are the likely advantages of the combined strategy. While a number of studies have provided experimental evidence in support of this concept, negative interference between phages and antibiotics have been reported as well. Neutral effects have also been observed, but in those cases, combined approaches may still be important for at least hampering the development of resistance. In any case, the choice of phage type and antibiotic as well as their mixing ratios must be given careful consideration when deciding for a dual antibacterial approach. The most frequently tested bacterium for a combined antibacterial treatment has been Pseudomonas aeruginosa, but encouraging results have also been reported for Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Enterococcus faecalis, and Burkholderia cepacia. Given the immense play area of conceivable phage-antibiotic combinations and their potential excess value, it is time to recapitulate of what has been achieved so far. This review therefore gathers and compares the results from most relevant studies in order to help researchers and clinicians in their strategies to combat multidrug resistant bacteria. Special attention is given to the selected bacterial model organisms, the phage families and genera employed, and the experimental design and evaluation (e.g., in vitro vs. in vivo models, biofilm vs. planktonic culture experiments, order and frequency of administration etc.). The presented data may serve as a framework for directed further experimental approaches to ultimately achieve a resolute challenge of multidrug resistant bacteria based on traditional antibiotics and phages.

Searching for Atrial Fibrillation Poststroke: A White Paper of the AF-SCREEN International Collaboration

Abstract: Cardiac thromboembolism attributed to atrial fibrillation (AF) is responsible for up to one-third of ischemic strokes. Stroke may be the first manifestation of previously undetected AF. Given the efficacy of oral anticoagulants in preventing AF-related ischemic strokes, strategies of searching for AF after a stroke using ECG monitoring followed by oral anticoagulation (OAC) treatment have been proposed to prevent recurrent cardioembolic strokes. This white paper by experts from the AF-SCREEN International Collaboration summarizes existing evidence and knowledge gaps on searching for AF after a stroke by using ECG monitoring. New AF can be detected by routine plus intensive ECG monitoring in approximately one-quarter of patients with ischemic stroke. It may be causal, a bystander, or neurogenically induced by the stroke. AF after a stroke is a risk factor for thromboembolism and a strong marker for atrial myopathy. After acute ischemic stroke, patients should undergo 72 hours of electrocardiographic monitoring to detect AF. The diagnosis requires an ECG of sufficient quality for confirmation by a health professional with ECG rhythm expertise. AF detection rate is a function of monitoring duration and quality of analysis, AF episode definition, interval from stroke to monitoring commencement, and patient characteristics including old age, certain ECG alterations, and stroke type. Markers of atrial myopathy (eg, imaging, atrial ectopy, natriuretic peptides) may increase AF yield from monitoring and could be used to guide patient selection for more intensive/prolonged poststroke ECG monitoring. Atrial myopathy without detected AF is not currently sufficient to initiate OAC. The concept of embolic stroke of unknown source is not proven to identify patients who have had a stroke benefitting from empiric OAC treatment. However, some embolic stroke of unknown source subgroups (eg, advanced age, atrial enlargement) might benefit more from non-vitamin K-dependent OAC therapy than aspirin. Fulfilling embolic stroke of unknown source criteria is an indication neither for empiric non-vitamin K-dependent OAC treatment nor for withholding prolonged ECG monitoring for AF. Clinically diagnosed AF after a stroke or a transient ischemic attack is associated with significantly increased risk of recurrent stroke or systemic embolism, in particular, with additional stroke risk factors, and requires OAC rather than antiplatelet therapy. The minimum subclinical AF duration required on ECG monitoring poststroke/transient ischemic attack to recommend OAC therapy is debated.

(Mis)Information Dissemination in WhatsApp: Gathering, Analyzing and Countermeasures

Abstract: WhatsApp has revolutionized the way people communicate and interact. It is not only cheaper than the traditional Short Message Service (SMS) communication but it also brings a new form of mobile communication: the group chats. Such groups are great forums for collective discussions on a variety of topics. In particular, in events of great social mobilization, such as strikes and electoral campaigns, WhatsApp group chats are very attractive as they facilitate information exchange among interested people. Yet, recent events have raised concerns about the spreading of misinformation in WhatsApp. In this work, we analyze information dissemination within WhatsApp, focusing on publicly accessible political-oriented groups, collecting all shared messages during major social events in Brazil: a national truck drivers' strike and the Brazilian presidential campaign. We analyze the types of content shared within such groups as well as the network structures that emerge from user interactions within and cross-groups. We then deepen our analysis by identifying the presence of misinformation among the shared images using labels provided by journalists and by a proposed automatic procedure based on Google searches. We identify the most important sources of the fake images and analyze how they propagate across WhatsApp groups and from/to other Web platforms.

The commonness of rarity: Global and future distribution of rarity across land plants.

Abstract: A key feature of life’s diversity is that some species are common but many more are rare. Nonetheless, at global scales, we do not know what fraction of biodiversity consists of rare species. Here, we present the largest compilation of global plant diversity to quantify the fraction of Earth’s plant biodiversity that are rare. A large fraction, ~36.5% of Earth’s ~435,000 plant species, are exceedingly rare. Sampling biases and prominent models, such as neutral theory and the k-niche model, cannot account for the observed prevalence of rarity. Our results indicate that (i) climatically more stable regions have harbored rare species and hence a large fraction of Earth’s plant species via reduced extinction risk but that (ii) climate change and human land use are now disproportionately impacting rare species. Estimates of global species abundance distributions have important implications for risk assessments and conservation planning in this era of rapid global change.