Differentiation of Candida dubliniensis from Candida albicans with the use of killer toxins

The aim of this study was to report the ability of killer toxins, previously used as biotyping techniques, as a new tool to differentiate C. albicans from C. dubliniensis. The susceptibility of C. albicans and C. dubliniensis to killer toxins ranged from 33.9 to 93.3% and from 6.67 to 93.3%, respectively.Avaliou-se a capacidade das toxinas killer, previamente utilizadas na biotipagem de C. albicans, como método para diferenciar C. albicans de C. dubliniensis. A susceptibilidade de C. albicans e C. dubliniensis às toxinas killer variou de 33,9% a 93,3% para C. albicans e de 6,67% a 93,3% para C. dubliniensis

Knowledge of dental surgeries on antimicrobials and bacterial resistance

Antimicrobials are often prescribed by dental surgeons for therapeutic and prophylactic reasons to treat orofacial infections. The inappropriate and indiscriminate use of these drugs can lead to the selection of resistant microorganisms, generating a public health problem. Because these drugs are used in all areas of dentistry, it is essential that dental surgeons have adequate knowledge of antimicrobials. Objective: this study aimed to verify the level of knowledge of dental surgeons on prescription of antimicrobials. Methodology: a structured questionnaire was applied to 242 dental surgeons who work in the city of Passo Fundo, Rio Grande do Sul, with demographic and specific questions about antibacterial prescription. The data obtained were tabulated in an Excel spreadsheet and exported to the statistical program StataSE 12 for statistical analysis. Results: among those interviewed, approximately 29% of dental surgeons used as a criterion for choosing an antimicrobial to be bactericidal, and as a method of avoiding bacterial resistance the majority chose to prescribe antimicrobial only when necessary. The primary drug of approximately 54% of respondents was Amoxicillin and, for patients allergic to penicillin, most would use Clindamycin. Conclusions: from the analysis of the responses, it can be concluded that dental surgeons have little knowledge about antimicrobials and what should be done to avoid bacterial resistance, being necessary an improvement in the criteria of the use and prescription of antimicrobials and a continuing education on this subject for professional to decrease the incidence of problems related to the prescription of these drugs

Infecções causadas por malassezia: novas abordagens

The genus Malassezia comprises lipophylic and lipodependent species that recently were reclassified with the description of four new species: M. globosa, M. obtuse, M. slooffiae and M. restricta. The species previously described are M. furfur, M. pachydermatis and M. sympodialis. These yeasts are associated to pathologies that include tinea versicolor, seborrheic dermatitis, atopic dermatitis, fungemias, among others. These diseases were previously thought to be caused exclusively by the species M. furfur. The taxonomical changes observed for the Malassezia species has led to the reassessment of the laboratory methodologies which were formerly used for the identification of the etiologic agent. Morphologic and physiologic variations for each species, termo-tolerance, the requirement for certain long-chain fatty acid sources, as well the composition and characteristics of their DNA are among themO gênero Malassezia compreende fungos leveduriformes lipofílicos e lipodependentes que recentemente sofreram mudanças em sua classificação taxonômica, com a introdução de quatro novas espécies: M. globosa, M. obtusa, M. slooffiae e M. restricta, além das espécies M. furfur, M. pachydermatis e M. sympodialis, anteriormente descritas. Estes fungos estão associados a vários quadros patológicos que incluem infecções como a pitiríase versicolor, dermatite seborréica, dermatite atópica, fungemia, entre outros. Estes quadros eram, até pouco tempo atrás, considerados exclusivamente causados pela espécie M. furfur. As mudanças na classificação taxonômica do gênero Malassezia levaram a uma reavaliação dos procedimentos laboratoriais utilizados para a identificação deste agente etiológico. Entre eles podemos citar o estudo e a caracterização morfológica das espécies, sua tolerância térmica, suas necessidades nutricionais para determinados tipos de ácidos graxos, bem como a composição e as características do DNA de cada uma delas

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

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