A2ML1 and otitis media: novel variants, differential expression, and relevant pathways

A genetic basis for otitis media is established, however, the role of rare variants in disease etiology is largely unknown. Previously a duplication variant within A2ML1 was identified as a significant risk factor for otitis media in an indigenous Filipino population and in US children. In this report exome and Sanger sequencing was performed using DNA samples from the indigenous Filipino population, Filipino cochlear implantees, US probands, Finnish, and Pakistani families with otitis media. Sixteen novel, damaging A2ML1 variants identified in otitis media patients were rare or low-frequency in population-matched controls. In the indigenous population, both gingivitis and A2ML1 variants including the known duplication variant and the novel splice variant c.4061 + 1 G>C were independently associated with otitis media. Sequencing of salivary RNA samples from indigenous Filipinos demonstrated lower A2ML1 expression according to the carriage of A2ML1 variants. Sequencing of additional salivary RNA samples from US patients with otitis media revealed differentially expressed genes that are highly correlated with A2ML1 expression levels. In particular, RND3 is upregulated in both A2ML1 variant carriers and high-A2ML1 expressors. These findings support a role for A2ML1 in keratinocyte differentiation within the middle ear as part of otitis media pathology and the potential application of ROCK inhibition in otitis media

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Swine infection by Streptococcus suis: a retrospective study Infecção em suínos por Streptococcus suis: estudo retrospectivo

The epidemic aspects of swine infections caused by Streptococcus suis were studied, focusing mainly on the occurrence of several serotypes. A total of 323 samples of S. suis were isolated from clinically ill animals, serotyped according to the co-agglutination procedure, and analyzed. The serotyping revealed that S. suis was present in several Brazilian states. The largest number was isolated from the states of Minas Gerais (62.5%), São Paulo (10.8%), and Paraná (9.3%). Serotype 2 was the most frequent (61.0%), followed by the serotypes 1, 3, 4, 7, and 8. The largest number of isolations was obtained from the brain (60.1%), followed by the lungs (10.4%). About 9.4% of the cases were due to septicemia.<br>Estudaram-se os aspectos epidêmicos das infecções de suínos causadas por Streptococcus suis, enfocando, principalmente, a ocorrência de diferentes sorotipos. Foram analisadas 323 amostras isoladas de animais clinicamente doentes, as quais foram sorotipadas de acordo com o procedimento de co-aglutinação. Foi verificado que S. suis está presente em vários estados brasileiros e o maior número de isolados originou-se dos estados de Minas Gerais (62,5%), São Paulo (10,8%) e Paraná (9,3%). O sorotipo 2 foi o mais freqüente (61.0%), seguido pelos sorotipos 1, 3, 4, 7 e 8. Os isolamentos foram obtidos principalmente de cérebro (60,1%) e pulmões (10,4%). Os casos de septicemia representaram 9,4%

TRY plant trait database, enhanced coverage and open access

Plant traits-the morphological, ahawnatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives