Probabilistic patterns of interaction: the effects of link-strength variability on food web structure

Patterns of species interactions affect the dynamics of food webs. An important component of species interactions that is rarely considered with respect to food webs is the strengths of interactions, which may affect both structure and dynamics. In natural systems, these strengths are variable, and can be quantified as probability distributions. We examined how variation in strengths of interactions can be described hierarchically, and how this variation impacts the structure of species interactions in predator-prey networks, both of which are important components of ecological food webs. The stable isotope ratios of predator and prey species may be particularly useful for quantifying this variability, and we show how these data can be used to build probabilistic predator-prey networks. Moreover, the distribution of variation in strengths among interactions can be estimated from a limited number of observations. This distribution informs network structure, especially the key role of dietary specialization, which may be useful for predicting structural properties in systems that are difficult to observe. Finally, using three mammalian predator-prey networks ( two African and one Canadian) quantified from stable isotope data, we show that exclusion of link-strength variability results in biased estimates of nestedness and modularity within food webs, whereas the inclusion of body size constraints only marginally increases the predictive accuracy of the isotope-based network. We find that modularity is the consequence of strong link-strengths in both African systems, while nestedness is not significantly present in any of the three predator-prey networks.

Push-out bond strengths of different dental cements used to cement glass fiber posts

Statement of problem: Since the introduction of glass fiber posts, irreversible vertical root fractures have become a rare occurrence; however, adhesive failure has become the primary failure mode. Purpose: The purpose of this study was to evaluate the push-out bond strength of glass fiber posts cemented with different luting agents on 3 segments of the root. Material and methods: Eighty human maxillary canines with similar root lengths were randomly divided into 8 groups (n=10) according to the cement assessed (Rely X luting, Luting and Lining, Ketac Cem, Rely X ARC, Biscem, Duo-link, Rely X U100, and Variolink II). After standardized post space preparation, the root dentin was pretreated for dualpolymerizing resin cements and untreated for the other cements. The mixed luting cement paste was inserted into post spaces with a spiral file and applied to the post surface that was seated into the canal. After 7 days, the teeth were sectioned perpendicular to their long axis into 1-mm-thick sections. The push-out test was performed at a speed of 0.5 mm/min until extrusion of the post occurred. The results were evaluated by 2-way ANOVA and the all pairwise multiple comparison procedures (Tukey test) (?=.05). Results: ANOVA showed that the type of interaction between cement and root location significantly influenced the push-out strength (P<.05). The highest push-out strength results with root location were obtained with Luting and Lining (S3) (19.5 ±4.9 MPa), Ketac Cem (S2) (18.6 ±5.5 MPa), and Luting and Lining (S1) (18.0 ±7.6 MPa). The lowest mean values were recorded with Variolink II (S1) (4.6 ±4.0 MPa), Variolink II (S2) (1.6 ±1.5 MPa), and Rely X ARC (S3) (0.9 ±1.1 MPa). Conclusions: Self-adhesive cements and glass ionomer cements showed significantly higher values compared to dual-polymerizing resin cements. In all root segments, dual-polymerizing resin cements provided significantly lower bond strength. Significant differences among root segments were found only for Duo-link cement.

Fiber Post Cementation Strategies: Effect of Mechanical Cycling on Push-out Bond Strength and Cement Polymerization Stress

Purpose: To evaluate the effect of mechanical cycling and cementation strategies on the push-out bond strength between fiber posts and root dentin and the polymerization stresses produced using three resin cements. Materials and Methods: Eighty bovine mandibular teeth were sectioned to a length of 16 mm, prepared to 12 mm, and embedded in self-curing acrylic resin. The specimens were then distributed into 8 groups (n = 10): Gr1 - Scotchbond Multi Purpose + RelyX ARC; Gr2 - Scotchbond Multi Purpose + RelyX ARC + mechanical cycling; Gr3 - AdheSE + Multilink Automix; Gr4 - AdheSE + Multilink Automix + mechanical cycling; Gr5 - phosphoric acid + RelyX U100 (self-adhesive cement); Gr6 - phosphoric acid+ RelyX U100 + mechanical cycling; Gr7 - RelyX U100; Gr8 - RelyX U100 + mechanical cycling. The values obtained from the push-out bond strength test were submitted to two-way ANOVA and Tukey's test (p = 0.05), while the values obtained from the polymerization stress test were subjected to one-way ANOVA and Tukey's test (alpha = 0.05). Results: Mechanical cycling did not affect the bond strength values (p = 0.236), while cementation strategies affected the push-out bond strength (p < 0.001). Luting with RelyX U100 and Scotch Bond Multi Purpose + RelyX ARC yielded higher push-out bond strength values. The polymerization stress results were affected by the factor "cement" (p = 0.0104): the self-adhesive cement RelyX U100 exhibited the lowest values, RelyX ARC resulted in the highest values, while Multi link Automix presented values statistically similar to the other two cements. Conclusion: The self-adhesive cement appears to be a good alternative for luting fiber posts due to the high push-out bond strengths and lower polymerization stress values.

Latent residual analysis in binary regression with skewed link

Model diagnostics is an integral part of model determination and an important part of the model diagnostics is residual analysis. We adapt and implement residuals considered in the literature for the probit, logistic and skew-probit links under binary regression. New latent residuals for the skew-probit link are proposed here. We have detected the presence of outliers using the residuals proposed here for different models in a simulated dataset and a real medical dataset.

Leptin as a link between the immune system and kidney-related diseases: leading actor or just a coadjuvant?

Food intake and nutritional status modify the physiological responses of the immune system to illness and infection and regulate the development of chronic inflammatory processes, such as kidney disease. Adipose tissue secretes immune-related proteins called adipokines that have pleiotropic effects on both the immune and neuroendocrine systems, linking metabolism and immune physiology. Leptin, an adipose tissue-derived adipokine, displays a variety of immune and physiological functions, and participates in several immune responses. Here, we review the current literature on the role of leptin in kidney diseases, linking adipose tissue and the immune system with kidney-related disorders. The modulation of this adipose hormone may have a major impact on the treatment of several immune- and metabolic-related kidney diseases.

Link prediction using a probabilistic description logic

Due to the growing interest in social networks, link prediction has received significant attention. Link prediction is mostly based on graph-based features, with some recent approaches focusing on domain semantics. We propose algorithms for link prediction that use a probabilistic ontology to enhance the analysis of the domain and the unavoidable uncertainty in the task (the ontology is specified in the probabilistic description logic crALC). The scalability of the approach is investigated, through a combination of semantic assumptions and graph-based features. We evaluate empirically our proposal, and compare it with standard solutions in the literature.