Child-OIDP index in Brazil: Cross-cultural adaptation and validation

Background: Oral health-related quality of life (OHRQoL) measures are being increasingly used to introduce dimensions excluded by normative measures. Consequently, there is a need for an index which evaluates children's OHRQoL validated for Brazilian population, useful for oral health needs assessments and for the evaluation of oral health programs, services and technologies. The aim of this study was to do a cross-cultural adaptation of the Child Oral Impacts on Daily Performances (Child-OIDP) index, and assess its reliability and validity for application among Brazilian children between the ages of eleven and fourteen. Methods: For cross-cultural adaptation, a translation/back-translation method integrated with expert panel reviews was applied. A total of 342 students from four public schools took part of the study. Results: Overall, 80.7% of the sample reported at least one oral impact in the last three months. Cronbach's alpha was 0.63, the weighted kappa 0.76, and the intraclass correlation coefficient (ICC) 0.79. The index had a significant association with self-reported health measurements (self-rated oral health, satisfaction with oral health, perceived dental treatment needs, self-rated general health; all p < 0.01). Conclusion: It was concluded that the Child-OIDP index is a measure of oral health-related quality of life that can be applied to Brazilian children

Incorporating costs, thresholds and spatial extents for selecting stream bioindicators in an ecotone between two Brazilian biodiversity hotspots

Biomonitoring is critical for characterizing and monitoring status, spatial patterns, and long-term trends in the ecological condition of freshwater ecosystems. The selection of cost-effective bioindicators is a critical step in establishing such monitoring programs. Key indicator considerations are a reliable response to anthropogenic disturbances, a high benefit-cost-ratio and sensitivity at multiple spatial extents. We evaluated non-linear responses of Ephemeroptera, Plecoptera and Trichoptera (EPT) and fish to the effects of native vegetation loss within buffers of 100 m and 1000 m and assessed the sampling and processing costs involved for each assemblage. We sampled 37 neotropical stream sites in the Formoso River network, a karstic region of the Bodoquena Plateau, midwest Brazil, lying in the ecotone between the Cerrado and Atlantic Forest biological hotspots. We used TITAN (threshold indicator taxa analysis) to identify six indicator taxa, four EPT genera and two fish species. The four EPT genera had low negative thresholds to native vegetation loss, whereas the two fish species had positive thresholds. Thresholds were lower for the 100 m buffers than the 1000 m buffers for EPT. The most sensitive taxon (Macronema, Trichoptera) had a threshold of 0% native vegetation loss in the 100 m buffers and nearly 40% in the 1000 m buffers. For taxa richness, we found no non-linear response to the effects of native vegetation loss for buffer extent nor assemblage. The total cost for EPT biomonitoring was US$3,616; whereas for fish, the total was US$ 1,901. Although fish were less expensive than EPT, they did not respond negatively to native vegetation loss and their positive threshold started at 48%, a level of vegetation loss that was highly disruptive of EPT. Therefore, we do not recommend using fish to monitor the effects of native vegetation loss on headwater streams in the Bodoquena Plateau. Although EPT monitoring costs 52% more than fish assemblage monitoring, it detected earlier impacts of the effects of native vegetation loss on stream biota, especially in the 100 m buffer. Therefore, EPT are more cost-effective early warning indicators for monitoring the effects of native vegetation loss in Bodoquena Plateau headwaters

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors

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

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

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

Lithium increases plasma brain-derived neurotrophic factor in acute bipolar mania: A preliminary 4-week study

Several studies have suggested an important role for brain-derived neurotrophic factor (BDNF) in the pathophysiology and therapeutics of bipolar disorder (BPD). The mechanisms underlying the therapeutic effects of lithium in BPD seem to involve a direct regulation of neurotrophic cascades. However, no clinical study evaluated the specific effects of lithium on BDNF levels in subjects with BPD. This study aims to investigate the effects of lithium monotherapy on BDNF levels in acute mania. Ten subjects with bipolar I disorder in a manic episode were evaluated at baseline and after 28 days of lithium therapy. Changes in plasma BDNF levels and Young Mania Rating Scale (YMRS) scores were analyzed. A significant increase in plasma BDNF levels was observed after 28 days of therapy with lithium monotherapy (510.9 +/- 127.1 pg/mL) compared to pre-treatment (406.3 +/- 69.5 pg/mL) (p = 0.03). Although it was not found a significant association between BDNF levels and clinical improvement (YMRS), 87% of responders presented an increase in BDNF levels after treatment with lithium. These preliminary data showed lithium`s direct effects on BDNF levels in bipolar mania, suggesting that short-term lithium treatment may activate neurotrophic cascades. Further studies with larger samples and longer period may confirm whether this biological effect is involved in the therapeutic efficacy of lithium in BPD. (C) 2011 Elsevier Ireland Ltd. All rights reserved.Espirita Hospital of Porto AlegreStanley Medical Research InstituteUSA (SMRI)Associacao Beneficente Alzira Denise Hertzog da Silva (ABADHS)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Institut Nacional de Ciencia e Tecnologia em Excitoxicidade e Neuroprotecao (INCTen