Micromorphological and hardness analyses of human and bovine sclerotic dentin: a comparative study

The purpose of this study was to test the hypothesis that both human and bovine sclerotic dentin have similar hardness properties, in addition to similar micromorphological characteristics. Sixteen teeth (8 human and 8 bovine) exhibiting exposed dentin in the incisal edge and showing characteristics typical of sclerosis were used. Vickers surface microhardness testing was conducted. Three areas of the dentin surface of each specimen were selected. All teeth were processed for scanning electron microscopy in order to estimate the amount (in percentage) of solid dentin on the sclerotic dentin surface. The data were compared by Student's t test (α = 0.05). The micromorphological and microhardness data were compared by Pearson's linear correlation test (α = 0.05). The mean percentages of solid dentin of human and bovine sclerotic dentin were similar (human 90.71 ± 0.83 and bovine 89.08 ± 0.81, p = 0.18). The mean microhardness value (VHN) of human sclerotic dentin was significantly higher than that of bovine sclerotic dentin (human 45.26 ± 2.92 and bovine 29.93 ± 3.83, p = 0.006). No correlation was found between the microhardness values and the amount of solid dentin in the sclerotic dentin, irrespective of the species considered (human R² = 0.0240, p = 0.714; bovine R² = 0.0017, p = 0.923; and combined R² = 0.038, p = 0.46). We concluded that although both bovine and human sclerotic dentin present a similar amount of solid tissue, human sclerotic dentin presents higher microhardness than bovine sclerotic dentin.(FAPESP) São Paulo Research Foundation(CAPES) Coordination for the Improvement of Higher Education Personne

Factors Associated with SARS-CoV-2 Infection among Oral Health Team Professionals

Objective: To analyze the factors associated with the SARS-CoV-2 infection among oral health professionals. Material and Methods: This was a cross-sectional study in the city of São Paulo, São Paulo State, Brazil. Professionals from three different categories were included: dental surgeons (DS), dental assistants (DA), and dental hygienists (DH). A questionnaire was created on a digital platform and sent via institutional email to each subject. The questionnaire contained 32 questions about sociodemographic, work, and behavior factors. The data about SARS-CoV-2 infection was confirmed through RT-PCR exams. Descriptive (absolute and relative frequencies) and inferential analyses (chi-squared or Fisher’s exact test) (p<0.05) were performed. Results: There was a SARS-CoV-2 infection prevalence of 3.8% for DS, 30.0% for DH, and 33.3% for DA. SARS-CoV-2 was associated with a lower income (p=0.027), a lower education level (p=0.011), the category of technical professionals (DA and DH) (p=0.025), and using public transportation to commute to work (p=0.009). Conclusion: Sociodemographic factors like lower income and education levels and work factors like job category and public transportation were associated with COVID-19 among professionals on the oral health teams

Factors Associated with SARS-CoV-2 Infection among Oral Health Team Professionals

Objective: To analyze the factors associated with the SARS-CoV-2 infection among oral health professionals. Material and Methods: This was a cross-sectional study in the city of São Paulo, São Paulo State, Brazil. Professionals from three different categories were included: dental surgeons (DS), dental assistants (DA), and dental hygienists (DH). A questionnaire was created on a digital platform and sent via institutional email to each subject. The questionnaire contained 32 questions about sociodemographic, work, and behavior factors. The data about SARS-CoV-2 infection was confirmed through RT-PCR exams. Descriptive (absolute and relative frequencies) and inferential analyses (chi-squared or Fisher’s exact test) (p<0.05) were performed. Results: There was a SARS-CoV-2 infection prevalence of 3.8% for DS, 30.0% for DH, and 33.3% for DA. SARS-CoV-2 was associated with a lower income (p=0.027), a lower education level (p=0.011), the category of technical professionals (DA and DH) (p=0.025), and using public transportation to commute to work (p=0.009). Conclusion: Sociodemographic factors like lower income and education levels and work factors like job category and public transportation were associated with COVID-19 among professionals on the oral health teams

Acute Exposure to Two Biocides Causes Morphological and Molecular Changes in the Gill Ciliary Epithelium of the Invasive Golden Mussel Limnoperna fortunei (Dunker, 1857)

Limnoperna fortunei, the golden mussel, is a bivalve mollusk considered an invader in South America. This species is responsible for ecological and economic damages due to its voluminous fouling capability. Chemical biocides such as MXD-100™ and sodium dichloroisocyanurate (NaDCC) are often used to control L. fortunei infestations in hydraulic systems. Thus, we proposed to investigate the effects of different periods (24, 48 and 72 h) of exposure to MXD-100™ (0.56 mg L−1) and NaDCC (1.5 mg L−1) on the gills of L. fortunei through morphological and molecular analyses. NaDCC promoted progressive morphological changes during the analyzed periods and only an upregulation of SOD and HSP70 expression during the first 24 h of exposure. MXD-100™ led to severe morphological changes from the first period of exposure, in addition to an upregulation of SOD, CAT, HSP70 and CYP expression during the first 24 h. In contrast, MXD-100™ led to a downregulation of CAT transcription between 24 and 48 h. In static conditions, NaDCC causes lethal damage after 72 h of exposure, and that exposure needs to be continuous to achieve the control of the species. Meanwhile, the MXD-100™ treatment presented several effects during the first 24 h, showing acute toxicity in a shorter period of time

Hexapoda Yearbook (Arthropoda: Mandibulata: Pancrustacea) Brazil 2020: the first annual production survey of new Brazilian species

This paper provided a list of all new Brazilian Hexapoda species described in 2020. Furthermore, based on the information extracted by this list, we tackled additional questions regarding the taxa, the specialists involved in the species descriptions as well as the journals in which those papers have been published. We recorded a total of 680 new Brazilian species of Hexapoda described in 2020, classified in 245 genera, 112 families and 18 orders. These 680 species were published in a total of 219 articles comprising 423 different authors residing in 27 countries. Only 30% of these authors are women, which demonstrates an inequality regarding sexes. In relation to the number of authors by species, the majority of the new species had two authors and the maximum of authors by species was five. We also found inequalities in the production of described species regarding the regions of Brazil, with Southeast and South leading. The top 10 institutions regarding productions of new species have four in the Southeast, two at South and with one ate North Region being the outlier of this pattern. Out of the total 219 published articles, Zootaxa dominated with 322 described species in 95 articles. The average impact factor was of 1.4 with only seven articles being published in Impact Factors above 3, indicating a hardship on publishing taxonomic articles in high-impact journals.The highlight of this paper is that it is unprecedent, as no annual record of Hexapoda species described was ever made in previous years to Brazil.Fil: Silva Neto, Alberto Moreira. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Lopes Falaschi, Rafaela. Universidade Estadual do Ponta Grossa; BrasilFil: Zacca, Thamara. Universidade Federal Do Rio de Janeiro. Museu Nacional; BrasilFil: Hipólito, Juliana. Universidade Federal da Bahia; BrasilFil: Costa Lima Pequeno, Pedro Aurélio. Universidade Federal de Roraima; BrasilFil: Alves Oliveira, João Rafael. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Oliveira Dos Santos, Roberto. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Heleodoro, Raphael Aquino. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Jacobina, Adaiane Catarina Marcondes. Universidade Federal do Paraná; BrasilFil: Somavilla, Alexandre. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Camargo, Alexssandro. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: de Oliveira Lira, Aline. Universidad Federal Rural Pernambuco; BrasilFil: Sampaio, Aline Amanda. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: da Silva Ferreira, André. Universidad Federal Rural Pernambuco; BrasilFil: Martins, André Luis. Universidade Federal do Paraná; BrasilFil: Figueiredo de Oliveira, Andressa. Universidade Federal do Mato Grosso do Sul; BrasilFil: Gonçalves da Silva Wengrat , Ana Paula. Universidade do Sao Paulo. Escola Superior de Agricultura Luiz de Queiroz; BrasilFil: Batista Rosa, Augusto Henrique. Universidade Estadual de Campinas; BrasilFil: Dias Corrêa, Caio Cezar. Universidade Federal Do Rio de Janeiro. Museu Nacional; BrasilFil: Costa De-Souza, Caroline. Museu Paraense Emilio Goeldi; BrasilFil: Anjos Dos Santos, Danielle. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Centro de Investigación Esquel de Montaña y Estepa Patagónica. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigación Esquel de Montaña y Estepa Patagónica; ArgentinaFil: Pacheco Cordeiro, Danilo. Instituto Nacional Da Mata Atlantica; BrasilFil: Silva Nogueira, David. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Almeida Marques, Dayse Willkenia. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Nunes Barbosa, Diego. Universidade Federal do Paraná; BrasilFil: Mello Mendes, Diego Matheus. Instituto de Desenvolvimento Sustentável Mamirauá; BrasilFil: Galvão de Pádua, Diego. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Silva Vilela, Diogo. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Gomes Viegas, Eduarda Fernanda. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Carneiro dos Santos, Eduardo. Universidade Federal do Paraná; BrasilFil: Rodrigues Fernandes, Daniell Rodrigo. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; Brasi

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

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution