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Institute
Objectives
To assess tooth discoloration induced by different hydraulic calcium silicate-based cements (HCSCs), including effects of blood and placement method.
Materials and methods
Eighty bovine teeth cut to a length of 18 mm (crown 8 mm, root 10 mm) were randomly assigned to 10 groups (n = 8), receiving orthograde apical plug treatment (APT). Apical plugs were 4 mm in length and made of ProRoot MTA (Dentsply), Medcem MTA (Medcem), TotalFill BC RRM Fast Set Putty (Brasseler), or Medcem Medical Portland Cement (Medcem) plus bismuth oxide (Bi2O3) with and without bovine blood. Further, orthograde (with or without preoperative adhesive coronal dentin sealing) and retrograde APT were compared. Teeth were obturated with gutta-percha and sealer, sealed with composite and stored in distilled water. Tooth color was measured on apical plug, gutta-percha/sealer, and crown surface before treatment versus 24 h, 1, 3, 6, 12, and 24 months after treatment by spectrophotometry. Color difference (ΔE) values were calculated and analyzed by Shapiro-Wilk test, ANOVA with post hoc tests, Friedman test, t test, and post hoc tests with Bonferroni correction (α = .05).
Results
Tooth discoloration occurred in all groups with no significant differences between HCSCs (p > .05). After 24 months, color changes were prominent on roots but insignificant on crowns. Blood contamination induced a significantly decreased luminescence (p < .05). Blood had a stronger impact on tooth color than Bi2O3. No relevant effects of retrograde placement (p > .05) or preoperative dentin sealing (p > .05) were detected.
Conclusions
Apical plugs of the tested HCSCs cause discoloration of bovine roots, but not discoloration of bovine tooth crowns within a 24-month period.
Clinical relevance
APT should be performed carefully while avoiding direct contact with the coronal dentin, and in that case no aesthetic impairments occur.
Aim
Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits.
Location
Tundra biome.
Time period
Data collected between 1964 and 2016.
Major taxa studied
295 tundra vascular plant species.
Methods
We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits.
Results
Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression.
Main conclusions
Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.
Motivation
The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.
Main types of variables included
The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.
Spatial location and grain
BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).
Time period and grain
BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.
Major taxa and level of measurement
BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
Software format
.csv and .SQL.
Background: Allergic rhinitis and asthma as single entities affect more boys than girls in childhood but more females in adulthood. However, it is unclear if this prevalence sex-shift also occurs in allergic rhinitis and concurrent asthma. Thus, our aim was to compare sex-specifc differences in the prevalence of coexisting allergic rhinitis and asthma in childhood, adolescence and adulthood.
Methods: Post-hoc analysis of systematic review with meta-analysis concerning sex-specific prevalence of allergic rhinitis. Using random-effects meta-analysis, we assessed male–female ratios for coexisting allergic rhinitis and asthma in children (0–10 years), adolescents (11–17) and adults (> 17). Electronic searches were performed using MEDLINE and EMBASE for the time period 2000–2014. We included population-based observational studies, reporting coexisting allergic rhinitis and asthma as outcome stratifed by sex. We excluded non-original or non-population-based studies, studies with only male or female participants or selective patient collectives.
Results: From a total of 6539 citations, 10 studies with a total of 93,483 participants met the inclusion criteria. The male–female ratios (95% CI) for coexisting allergic rhinitis and asthma were 1.65 (1.52; 1.78) in children (N = 6 studies), 0.61 (0.51; 0.72) in adolescents (N = 2) and 1.03 (0.79; 1.35) in adults (N = 2). Male–female ratios for allergic rhinitis only were 1.25 (1.19; 1.32, N = 5) in children, 0.80 (0.71; 0.89, N = 2) in adolescents and 0.98 (0.74; 1.30, N = 2) in adults, respectively.
Conclusions: The prevalence of coexisting allergic rhinitis and asthma shows a clear male predominance in childhood and seems to switch to a female predominance in adolescents. This switch was less pronounced for allergic rhinitis only.
Objective: The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the "Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder" scale currently used in the Consortium on Lithium Genetics (ConLiGen) study.
Materials and Methods: Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (\(\kappa\))] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling.
Results: Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (\(\kappa\) = 0.66 and \(\kappa\) = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (\(ICC_1 = 0.71\) and \(ICC_2 = 0.75\), respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders).
Conclusions: We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.