Can different stages of leprosy treatment influence the profile of oral health? Oral status in leprosy

The aim of study was to evaluate the oral health status, salivary flow and halitosis among individuals diagnosed with leprosy as compared with healthy subjects. A sample of 160 individuals was allocated into four groups, as follows: (G1) individuals with complete leprosy treatment; (G2) individuals diagnosed with leprosy and under multi-drug therapy; (G3) individuals diagnosed with leprosy not yet under treatment; and (G4) healthy individuals. Then individuals were submitted to periodontal clinical examination (visible plaque index, bleeding index, depth of probing and clinical attachment level); DMFT index (decayed-missing-filled teeth index); evaluation of salivary flow and halitosis using a halimeter equipment (Interscan Corp, Chatsworth, CA, USA). The data were analyzed using Kruskal-Wallis and chi-square tests. The mean DMFT was found to be higher than 6.6, which is considered very high, with no significant difference between groups (P>0.05). As for salivary flow, 76.2% of the subjects presented normal flow rates, while 10% and 13.7% showed low and very low salivary flow rates, respectively, with hyposalivation being mostly observed in Groups 1 and 2. The highest prevalence of noticeable odor was found in healthy individuals (G4), and the most prevalent periodontal diagnosis was gingivitis (63.1%) in Group 3 (individuals with leprosy not yet under multi-drug therapy) followed by periodontitis (25%) in Group 1 (individuals who had completed leprosy treatment). It was observed that individuals with a history of leprosy present poor oral health similar to that of systemically healthy individuals

Mapping QTL for protein and oil content in soybean

O objetivo deste trabalho foi detectar e mapear locos de caracteres quantitativos (QTL) que afetam os conteúdos de proteína e óleo em soja (Glycine max L. Merr.). Plantas F2, derivadas do cruzamento entre a linhagem CS3032PTA276 e a variedade UFVS2012, foram cultivadas em casa de vegetação e forneceram as folhas para extração e análise de DNA. Quarenta e oito marcadores microssatélites (SSR) polimórficos foram avaliados na população F2. A avaliação dos fenótipos foi realizada em 207 famílias das progênies F2:3, em um delineamento em blocos ao acaso, com três repetições, conduzido em Viçosa, MG, em 2006. Foram detectados quatro QTL associados ao conteúdo de proteína, nos grupos de ligação D1a, G, A1, e I, e três QTL associados ao conteúdo de óleo, nos grupos A1, I e O. A variação fenotípica explicada pelos QTL variou de 6,24 a 18,94% e 17,26 a 25,93%, respectivamente, para os conteúdos de proteína e óleo. Foram detectados novos QTL associados aos conteúdos de proteína e óleo, além dos previamente relatados em outros estudos. Regiões distintas das atualmente conhecidas podem estar envolvidas no controle genético do teor de proteína e óleo na soja.The objective of this study was to detect and map quantitative trait loci (QTL) affecting soybean (Glycine max L. Merr.) protein and oil contents. F2 plants, derived from the cross between the CS3032PTA276 line and the variety UFVS2012, were grown in a greenhouse and provided the leaves for DNA extraction and analysis. Forty-eight polymorphic microsatelite markers (SSR) were evaluated in the F2 population. Evaluation of the phenotype was performed in 207 families from F2:3 progenies, in a complete block design with three replicates, carried out in Viçosa, MG, Brazil, in 2006. Four QTL associated with protein content, in linkage groups D1a, G, A1, and I, and three QTL for oil content in groups A1, I and O were identified. Phenotypic variation for protein and oil explained by QTL ranged from 6.24 to 18.94% and 17.26 to 25.93%, respectively. New QTL associated with protein and oil contents were detected, besides those previously reported in other studies. Other regions may be involved in the genetic control of protein and oil contents in soybean besides those already known

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

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

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

Analysis of Metal Contents in Portland Type V and MTA-Based Cements

The aim of this study was to determine, by Atomic Absorption Spectrometry (AAS), the concentration levels of 11 metals in Type V gray and structural white PC, ProRoot MTA, and MTA Bio. Samples, containing one gram of each tested cement, were prepared and transferred to a 100 mL Teflon tube with a mixture of 7.0 mL of nitric acid and 21 mL of hydrochloric acid. After the reaction, the mixture was filtered and then volumed to 50 mL of distilled water. For each metal, specific patterns were determined from universal standards. Arsenic quantification was performed by hydride generator. The analysis was performed five times and the data were statistically analyzed at 5% level of significance. Only the cadmium presented concentration levels of values lower than the quantification limit of the device. The AAS analysis showed increased levels of calcium, nickel, and zinc in structural white PC. Type V PC presented the greatest concentration levels of arsenic, chromium, copper, iron, lead, and manganese (P<0.05). Bismuth was found in all cements, and the lowest concentration levels were observed in Portland cements, while the highest were observed in ProRoot MTA. Both PC and MTA-based cements showed evidence of metals inclusion