Dental Health and Mortality in People With End-Stage Kidney Disease Treated With Hemodialysis: A Multinational Cohort Study

Background Dental disease is more extensive in adults with chronic kidney disease, but whether dental health and behaviors are associated with survival in the setting of hemodialysis is unknown. Study Design Prospective multinational cohort. Setting & Participants 4,205 adults treated with long-term hemodialysis, 2010 to 2012 (Oral Diseases in Hemodialysis [ORAL-D] Study). Predictors Dental health as assessed by a standardized dental examination using World Health Organization guidelines and personal oral care, including edentulousness; decayed, missing, and filled teeth index; teeth brushing and flossing; and dental health consultation. Outcomes All-cause and cardiovascular mortality at 12 months after dental assessment. Measurements Multivariable-adjusted Cox proportional hazards regression models fitted with shared frailty to account for clustering of mortality risk within countries. Results During a mean follow-up of 22.1 months, 942 deaths occurred, including 477 cardiovascular deaths. Edentulousness (adjusted HR, 1.29; 95% CI, 1.10-1.51) and decayed, missing, or filled teeth score ≥ 14 (adjusted HR, 1.70; 95% CI, 1.33-2.17) were associated with early all-cause mortality, while dental flossing, using mouthwash, brushing teeth daily, spending at least 2 minutes on oral hygiene daily, changing a toothbrush at least every 3 months, and visiting a dentist within the past 6 months (adjusted HRs of 0.52 [95% CI, 0.32-0.85], 0.79 [95% CI, 0.64-0.97], 0.76 [95% CI, 0.58-0.99], 0.84 [95% CI, 0.71-0.99], 0.79 [95% CI, 0.65-0.95], and 0.79 [95% CI, 0.65-0.96], respectively) were associated with better survival. Results for cardiovascular mortality were similar. Limitations Convenience sample of clinics. Conclusions In adults treated with hemodialysis, poorer dental health was associated with early death, whereas preventive dental health practices were associated with longer survival

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

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazonia Sustentavel, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far.Keywords: Social–ecological systems, Tropical forests, Land use, Interdisciplinary research, Sustainability, Trade-off

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

Transcriptional regulation of the lignin biosynthetic pathway revisited: new players and insights

The discovery that AC elements coordinated the regulation of genes belonging to the entire lignin biosynthetic pathway was the first breakthrough in understanding how lignin biosynthesis is regulated. Since then, tremendous progress has been made in the identification and characterization of many transcription factors (TFs) that regulate the genes of the phenylpropanoid branch pathway leading to lignin. A major breakthrough consisted in the discovery of a hierarchical transcriptional network regulating the biosynthesis of lignified secondary walls (SWs) in Arabidopsis. The NAC TFs (VND/NST/SND) work as the first layer of master switches activating the whole SW biosynthetic network through the regulation of a cascade of downstream TFs. Among these, MYB46/83 act as a second layer of master switches. Recent findings, however, reveal that the regulation of SW formation is far more complex than initially thought, involving both positive and negative regulators, dual function regulators, feedback loops, combinatorial complexes and cross talk between pathways. Finally, because of the great potential that lignocellulosic biomass represents for the production of bioenergy, there is a great interest in further elucidating the molecular mechanisms underlying the regulation of lignified SW and subsequently applying this knowledge to improve their saccharification potential for the generation of biofuels61173218sem informaçã

Transcriptional Regulation of the Lignin Biosynthetic Pathway Revisited: New Players and Insights

The discovery that AC elements coordinated the regulation of genes belonging to the entire lignin biosynthetic pathway was the first breakthrough in understanding how lignin biosynthesis is regulated. Since then, tremendous progress has been made in the identification and characterization of many transcription factors (TFs) that regulate the genes of the phenylpropanoid branch pathway leading to lignin. A major breakthrough consisted in the discovery of a hierarchical transcriptional network regulating the biosynthesis of lignified secondary walls (SWs) in Arabidopsis. The NAC TFs (VND/NST/SND) work as the first layer of master switches activating the whole SW biosynthetic network through the regulation of a cascade of downstream TFs. Among these, MYB46/83 act as a second layer of master switches. Recent findings, however, reveal that the regulation of SW formation is far more complex than initially thought, involving both positive and negative regulators, dual function regulators, feedback loops, combinatorial complexes and cross talk between pathways. Finally, because of the great potential that lignocellulosic biomass represents for the production of bioenergy, there is a great interest in further elucidating the molecular mechanisms underlying the regulation of lignified SW and subsequently applying this knowledge to improve their saccharification potential for the generation of biofuels.6117321

Reference genes for high-throughput quantitative reverse transcription-PCR analysis of gene expression in organs and tissues of Eucalyptus grown in various environmental conditions

Interest in the genomics of Eucalyptus has skyrocketed thanks to the recent sequencing of the genome of Eucalyptus grandis and to a growing number of large-scale transcriptomic studies. Quantitative reverse transcription-PCR (RT-PCR) is the method of choice for gene expression analysis and can now also be used as a high-throughput method. The selection of appropriate internal controls is becoming of utmost importance to ensure accurate expression results in Eucalyptus. To this end, we selected 21 candidate reference genes and used high-throughput microfluidic dynamic arrays to assess their expression among a large panel of developmental and environmental conditions with a special focus on wood-forming tissues. We analyzed the expression stability of these genes by using three distinct statistical algorithms (geNorm, NormFinder and ΔCt), and used principal component analysis to compare methods and rankings. We showed that the most stable genes identified depended not only on the panel of biological samples considered but also on the statistical method used. We then developed a comprehensive integration of the rankings generated by the three methods and identified the optimal reference genes for 17 distinct experimental sets covering 13 organs and tissues, as well as various developmental and environmental conditions. The expression patterns of Eucalyptus master genes EgMYB1 and EgMYB2 experimentally validated our selection. Our findings provide an important resource for the selection of appropriate reference genes for accurate and reliable normalization of gene expression data in the organs and tissues of Eucalyptus trees grown in a range of conditions including abiotic stresses