Influence of lip closure on alveolar cleft width in patients with cleft lip and palate

<p>Abstract</p> <p>Background</p> <p>The influence of surgery on growth and stability after treatment in patients with cleft lip and palate are topics still under discussion. The aim of the present study was to investigate the influence of early lip closure on the width of the alveolar cleft using dental casts.</p> <p>Methods</p> <p>A total of 44 clefts were investigated using plaster casts, 30 unilateral and 7 bilateral clefts. All infants received a passive molding plate a few days after birth. The age at the time of closure of the lip was 2.1 month in average (range 1-6 months). Plaster casts were obtained at the following stages: shortly after birth, prior to lip closure, prior to soft palate closure. We determined the width of the alveolar cleft before lip closure and prior to soft palate closure measuring the alveolar cleft width from the most lateral point of the premaxilla/anterior segment to the most medial point of the smaller segment.</p> <p>Results</p> <p>After lip closure 15 clefts presented with a width of 0 mm, meaning that the mucosa of the segments was almost touching one another. 19 clefts showed a width of up to 2 mm and 10 clefts were still over 2 mm wide. This means a reduction of 0% in 5 clefts, of 1-50% in 6 clefts, of 51-99% in 19 clefts, and of 100% in 14 clefts.</p> <p>Conclusions</p> <p>Early lip closure reduces alveolar cleft width. In most cases our aim of a remaining cleft width of 2 mm or less can be achieved. These are promising conditions for primary alveolar bone grafting to restore the dental bony arch.</p

Blocking representation in the ERA-Interim driven EURO-CORDEX RCMs

While Regional Climate Models (RCMs) have been shown to yield improved simulations compared to General Circulation Model (GCM), their representation of large-scale phenomena like atmospheric blocking has been hardly addressed. Here, we evaluate the ability of RCMs to simulate blocking situations present in their reanalysis driving data and analyse the associated impacts on anomalies and biases of European 2-m air temperature (TAS) and precipitation rate (PR). Five RCM runs stem from the EURO-CORDEX ensemble while three RCMs are WRF models with different nudging realizations, all of them driven by ERA-Interim for the period 1981?2010. The detected blocking systems are allocated to three sectors of the Euro-Atlantic region, allowing for a characterization of distinctive blocking-related TAS and PR anomalies. Our results indicate some misrepresentation of atmospheric blocking over the EURO-CORDEX domain, as compared to the driving reanalysis. Most of the RCMs showed fewer blocks than the driving data, while the blocking misdetection was negligible for RCMs strongly conditioned to the driving data. A higher resolution of the RCMs did not improve the representation of atmospheric blocking. However, all RCMs are able to reproduce the basic anomaly structure of TAS and PR connected to blocking. Moreover, the associated anomalies do not change substantially after correcting for the misrepresentation of blocking in RCMs. The overall model bias is mainly determined by pattern biases in the representations of surface parameters during non-blocking situations. Biases in blocking detections tend to have a secondary influence in the overall bias due to compensatory effects of missed blockings and non-blockings. However, they can lead to measurable effects in the presence of a strong blocking underestimation.This work was funded by the Austrian Science Fund (FWF) under the project: Understanding Contrasts in high Mountain hydrology in Asia (UNCOMUN: I 1295-N29). This research was supported by the Faculty of Environmental, Regional and Educational Sciences (URBI), University of Graz, as well as the Federal Ministry of Science, Research and Economy (BMWFW) by funding the OeAD Grant Marietta Blau. This work was partially supported (JMG and SH) by the project MULTI-SDM (CGL2015-66583- R, MINECO/FEDER). DB was supported by the PALEOSTRAT (CGL2015-69699-R) project funded by the Spanish Ministry of Economy and Competitiveness (MINECO)

Analysis of rainfall seasonality from observations and climate models

Two new indicators of rainfall seasonality based on information entropy, the relative entropy (RE) and the dimensionless seasonality index (DSI), together with the mean annual rainfall, are evaluated on a global scale for recently updated precipitation gridded datasets and for historical simulations from coupled atmosphere--ocean general circulation models. The RE provides a measure of the number of wet months and, for precipitation regimes featuring a distinct wet and dry season, it is directly related to the duration of the wet season. The DSI combines the rainfall intensity with its degree of seasonality and it is an indicator of the extent of the global monsoon region. We show that the RE and the DSI are fairly independent of the time resolution of the precipitation data, thereby allowing objective metrics for model intercomparison and ranking. Regions with different precipitation regimes are classified and characterized in terms of RE and DSI. Comparison of different land observational datasets reveals substantial difference in their local representation of seasonality. It is shown that two-dimensional maps of RE provide an easy way to compare rainfall seasonality from various datasets and to determine areas of interest. Models participating to the Coupled Model Intercomparison Project platform, Phase 5, consistently overestimate the RE over tropical Latin America and underestimate it in West Africa, western Mexico and East Asia. It is demonstrated that positive RE biases in a general circulation model are associated with excessively peaked monthly precipitation fractions, too large during the wet months and too small in the months preceding and following the wet season; negative biases are instead due, in most cases, to an excess of rainfall during the premonsoonal months

Integrating social–ecological vulnerability assessments with climate forecasts to improve local climate adaptation planning for coral reef fisheries in Papua New Guinea

A major gap exists in integrating climate projections and social–ecological vulnerability analyses at scales that matter, which has affected local-scale adaptation planning and actions to date. We address this gap by providing a novel methodology that integrates information on: (i) the expected future climate, including climate-related extreme events, at the village level; (ii) an ecological assessment of the impacts of these climate forecasts on coral reefs; and (iii) the social adaptive capacity of the artisanal fishers, to create an integrated vulnerability assessment on coastal communities in five villages in Papua New Guinea. We show that, despite relatively proximate geographies, there are substantial differences in both the predicted extreme rainfall and temperature events and the social adaptive capacity among the five fishing-dependent communities, meaning that they have likely different vulnerabilities to future climate change. Our methodology shows that it is possible to capture social information and integrate this with climate and ecological modeling in ways that are best suited to address the impacts of climate-mediated environmental changes currently underway across different scales