Sticking under wet conditions: the remarkable attachment abilities of the torrent frog, staurois guttatus

Tree frogs climb smooth surfaces utilising capillary forces arising from an air-fluid interface around their toe pads, whereas torrent frogs are able to climb in wet environments near waterfalls where the integrity of the meniscus is at risk. This study compares the adhesive capabilities of a torrent frog to a tree frog, investigating possible adaptations for adhesion under wet conditions. We challenged both frog species to cling to a platform which could be tilted from the horizontal to an upside-down orientation, testing the frogs on different levels of roughness and water flow. On dry, smooth surfaces, both frog species stayed attached to overhanging slopes equally well. In contrast, under both low and high flow rate conditions, the torrent frogs performed significantly better, even adhering under conditions where their toe pads were submerged in water, abolishing the meniscus that underlies capillarity. Using a transparent platform where areas of contact are illuminated, we measured the contact area of frogs during platform rotation under dry conditions. Both frog species not only used the contact area of their pads to adhere, but also large parts of their belly and thigh skin. In the tree frogs, the belly and thighs often detached on steeper slopes, whereas the torrent frogs increased the use of these areas as the slope angle increased. Probing small areas of the different skin parts with a force transducer revealed that forces declined significantly in wet conditions, with only minor differences between the frog species. The superior abilities of the torrent frogs were thus due to the large contact area they used on steep, overhanging surfaces. SEM images revealed slightly elongated cells in the periphery of the toe pads in the torrent frogs, with straightened channels in between them which could facilitate drainage of excess fluid underneath the pad

On the reflection of magnon bound states

We investigate the reflection of two-particle bound states of a free open string in the light-cone AdS_5 x S^5 string sigma model, for large angular momentum J=J_56 and ending on a D7 brane which wraps the entire AdS_5 and a maximal S^3 of S^5. We use the superspace formalism to analyse fundamental and two-particle bound states in the cases of supersymmetry-preserving and broken-supersymmetry boundaries. We find the boundary S-matrices corresponding to bound states both in the bulk and on the boundary.Comment: 35 pages, v2: few typos and ref corrected, accepted for publication in JHE

Reflection algebra, Yangian symmetry and bound-states in AdS/CFT

We present the `Heisenberg picture' of the reflection algebra by explicitly constructing the boundary Yangian symmetry of an AdS/CFT superstring which ends on a boundary with non-trivial degrees of freedom and which preserves the full bulk Lie symmetry algebra. We also consider the spectrum of bulk and boundary states and some automorphisms of the underlying algebras.Comment: 31 page, 8 figures. Updated versio

PPARα L162V underlies variation in serum triglycerides and subcutaneous fat volume in young males

<p>Abstract</p> <p>Background</p> <p>Of the five sub-phenotypes defining metabolic syndrome, all are known to have strong genetic components (typically 50–80% of population variation). Studies defining genetic predispositions have typically focused on older populations with metabolic syndrome and/or type 2 diabetes. We hypothesized that the study of younger populations would mitigate many confounding variables, and allow us to better define genetic predisposition loci for metabolic syndrome.</p> <p>Methods</p> <p>We studied 610 young adult volunteers (average age 24 yrs) for metabolic syndrome markers, and volumetric MRI of upper arm muscle, bone, and fat pre- and post-unilateral resistance training.</p> <p>Results</p> <p>We found the PPARα L162V polymorphism to be a strong determinant of serum triglyceride levels in young White males, where carriers of the V allele showed 78% increase in triglycerides relative to L homozygotes (LL = 116 ± 11 mg/dL, LV = 208 ± 30 mg/dL; p = 0.004). Men with the V allele showed lower HDL (LL = 42 ± 1 mg/dL, LV = 34 ± 2 mg/dL; p = 0.001), but women did not. Subcutaneous fat volume was higher in males carrying the V allele, however, exercise training increased fat volume of the untrained arm in V carriers, while LL genotypes significantly decreased in fat volume (LL = -1,707 ± 21 mm³, LV = 17,617 ± 58 mm³; p = 0.002), indicating a systemic effect of the V allele on adiposity after unilateral training. Our study suggests that the primary effect of PPARα L162V is on serum triglycerides, with downstream effects on adiposity and response to training.</p> <p>Conclusion</p> <p>Our results on association of PPARα and triglycerides in males showed a much larger effect of the V allele than previously reported in older and less healthy populations. Specifically, we showed the V allele to increase triglycerides by 78% (p = 0.004), and this single polymorphism accounted for 3.8% of all variation in serum triglycerides in males (p = 0.0037).</p

PMeS: Prediction of Methylation Sites Based on Enhanced Feature Encoding Scheme

Protein methylation is predominantly found on lysine and arginine residues, and carries many important biological functions, including gene regulation and signal transduction. Given their important involvement in gene expression, protein methylation and their regulatory enzymes are implicated in a variety of human disease states such as cancer, coronary heart disease and neurodegenerative disorders. Thus, identification of methylation sites can be very helpful for the drug designs of various related diseases. In this study, we developed a method called PMeS to improve the prediction of protein methylation sites based on an enhanced feature encoding scheme and support vector machine. The enhanced feature encoding scheme was composed of the sparse property coding, normalized van der Waals volume, position weight amino acid composition and accessible surface area. The PMeS achieved a promising performance with a sensitivity of 92.45%, a specificity of 93.18%, an accuracy of 92.82% and a Matthew’s correlation coefficient of 85.69% for arginine as well as a sensitivity of 84.38%, a specificity of 93.94%, an accuracy of 89.16% and a Matthew’s correlation coefficient of 78.68% for lysine in 10-fold cross validation. Compared with other existing methods, the PMeS provides better predictive performance and greater robustness. It can be anticipated that the PMeS might be useful to guide future experiments needed to identify potential methylation sites in proteins of interest. The online service is available at http://bioinfo.ncu.edu.cn/inquiries_PMeS.aspx