Stable and unstable cadherin dimers: mechanisms of formation and roles in cell adhesion

Numerous attempts to elucidate the strength of cadherin dimerization that mediates intercellular adhesion have produced controversial and inconclusive results. To clarify this issue, we compared E-cadherin dimerization on the surface of living cells with how the same process unfolds on agarose beads. In both cases, dimerization was monitored by the same site-specific cross-linking assay, greatly simplifying data interpretation. We showed that on the agarose surface under physiological conditions, E-cadherin produced a weak dimer that immediately dissociated after the depletion of calcium ions. However, either at pH 5 or in the presence of cadmium ions, E-cadherin produced a strong dimer that was unable to dissociate upon calcium depletion. Both types of dimers were W156-dependent. Remarkably, only the strong dimer was found on the surface of living cells. We also showed that the intracellular cadherin region, the clustering of which through catenins had been proposed as stabilizer of weak intercadherin interactions, was not needed, in fact, for cadherin junction assembly. Taken together, our data present convincing evidence that cadherin adhesion is based on high-affinity cadherin–cadherin interactions

Scalar-tensor cosmology at the general relativity limit: Jordan vs Einstein frame

We consider the correspondence between the Jordan frame and the Einstein frame descriptions of scalar-tensor theory of gravitation. We argue that since the redefinition of the scalar field is not differentiable at the limit of general relativity the correspondence between the two frames is lost at this limit. To clarify the situation we analyse the dynamics of the scalar field in different frames for two distinct scalar-tensor cosmologies with specific coupling functions and demonstrate that the corresponding scalar field phase portraits are not equivalent for regions containing the general relativity limit. Therefore the answer to the question whether general relativity is an attractor for the theory depends on the choice of the frame.Comment: 16 pages, 8 figures, version appeared in PR

A Robust Color Image Watermarking Scheme Using Entropy and QR Decomposition

Internet has affected our everyday life drastically. Expansive volumes of information are exchanged over the Internet consistently which causes numerous security concerns. Issues like content identification, document and image security, audience measurement, ownership, copyrights and others can be settled by using digital watermarking. In this work, robust and imperceptible non-blind color image watermarking algorithm is proposed, which benefit from the fact that watermark can be hidden in different color channel which results into further robustness of the proposed technique to attacks. Given method uses some algorithms such as entropy, discrete wavelet transform, Chirp z-transform, orthogonal-triangular decomposition and Singular value decomposition in order to embed the watermark in a color image. Many experiments are performed using well-known signal processing attacks such as histogram equalization, adding noise and compression. Experimental results show that proposed scheme is imperceptible and robust against common signal processing attacks

Key exchange with the help of a public ledger

Blockchains and other public ledger structures promise a new way to create globally consistent event logs and other records. We make use of this consistency property to detect and prevent man-in-the-middle attacks in a key exchange such as Diffie-Hellman or ECDH. Essentially, the MitM attack creates an inconsistency in the world views of the two honest parties, and they can detect it with the help of the ledger. Thus, there is no need for prior knowledge or trusted third parties apart from the distributed ledger. To prevent impersonation attacks, we require user interaction. It appears that, in some applications, the required user interaction is reduced in comparison to other user-assisted key-exchange protocols

Scalar-tensor cosmologies: fixed points of the Jordan frame scalar field

We study the evolution of homogeneous and isotropic, flat cosmological models within the general scalar-tensor theory of gravity with arbitrary coupling function and potential. After introducing the limit of general relativity we describe the details of the phase space geometry. Using the methods of dynamical systems for the decoupled equation of the Jordan frame scalar field we find the fixed points of flows in two cases: potential domination and matter domination. We present the conditions on the mathematical form of the coupling function and potential which determine the nature of the fixed points (attractor or other). There are two types of fixed points, both are characterized by cosmological evolution mimicking general relativity, but only one of the types is compatible with the Solar System PPN constraints. The phase space structure should also carry over to the Einstein frame as long as the transformation between the frames is regular which however is not the case for the latter (PPN compatible) fixed point.Comment: 21 pages, 4 figures, some comments and references adde

Proceedings of the inaugural International Summit for Medical Nutrition Education and Research

© 2016 The Royal Society for Public Health Medical Nutrition Education (MNE) has been identified as an area with potential public health impact. Despite countries having distinctive education systems, barriers and facilitators to effective MNE are consistent across borders, demanding a common platform to initiate global programmes. A shared approach to supporting greater MNE is ideal to support countries to work together. In an effort to initiate this process, the Need for Nutrition Education/Innovation Programme group, in association with their strategic partners, hosted the inaugural International Summit on Medical Nutrition Education and Research on August 8, 2015 in Cambridge, UK. Speakers from the UK, the USA, Canada, Australia, New Zealand, Italy, and India provided insights into their respective countries including their education systems, inherent challenges, and potential solutions across two main themes: (1) Medical Nutrition Education, focused on best practice examples in competencies and assessment; and (2) Medical Nutrition Research, discussing how to translate nutrition research into education opportunities. The Summit identified shared needs across regions, showcased examples of transferrable strategies and identified opportunities for collaboration in nutrition education for healthcare (including medical) professionals. These proceedings highlight the key messages presented at the Summit and showcase opportunities for working together towards a common goal of improvement in MNE to improve public health at large

Shear turbulence in the high-wind Southern Ocean using direct measurements

Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 52(10), (2022): 2325–2341, https://doi.org/10.1175/jpo-d-21-0015.1.The ocean surface boundary layer is a gateway of energy transfer into the ocean. Wind-driven shear and meteorologically forced convection inject turbulent kinetic energy into the surface boundary layer, mixing the upper ocean and transforming its density structure. In the absence of direct observations or the capability to resolve subgrid-scale 3D turbulence in operational ocean models, the oceanography community relies on surface boundary layer similarity scalings (BLS) of shear and convective turbulence to represent this mixing. Despite their importance, near-surface mixing processes (and ubiquitous BLS representations of these processes) have been undersampled in high-energy forcing regimes such as the Southern Ocean. With the maturing of autonomous sampling platforms, there is now an opportunity to collect high-resolution spatial and temporal measurements in the full range of forcing conditions. Here, we characterize near-surface turbulence under strong wind forcing using the first long-duration glider microstructure survey of the Southern Ocean. We leverage these data to show that the measured turbulence is significantly higher than standard shear-convective BLS in the shallower parts of the surface boundary layer and lower than standard shear-convective BLS in the deeper parts of the surface boundary layer; the latter of which is not easily explained by present wave-effect literature. Consistent with the CBLAST (Coupled Boundary Layers and Air Sea Transfer) low winds experiment, this bias has the largest magnitude and spread in the shallowest 10% of the actively mixing layer under low-wind and breaking wave conditions, when relatively low levels of turbulent kinetic energy (TKE) in surface regime are easily biased by wave events.This paper is VIMS Contribution 4103. Computational resources were provided by the VIMS Ocean-Atmosphere and Climate Change Research Fund. AUSSOM was supported by the OCE Division of the National Science Foundation (1558639)

Supervised Domain Adaptation using Graph Embedding

Getting deep convolutional neural networks to perform well requires a large amount of training data. When the available labelled data is small, it is often beneficial to use transfer learning to leverage a related larger dataset (source) in order to improve the performance on the small dataset (target). Among the transfer learning approaches, domain adaptation methods assume that distributions between the two domains are shifted and attempt to realign them. In this paper, we consider the domain adaptation problem from the perspective of dimensionality reduction and propose a generic framework based on graph embedding. Instead of solving the generalised eigenvalue problem, we formulate the graph-preserving criterion as a loss in the neural network and learn a domain-invariant feature transformation in an end-to-end fashion. We show that the proposed approach leads to a powerful Domain Adaptation framework; a simple LDA-inspired instantiation of the framework leads to state-of-the-art performance on two of the most widely used Domain Adaptation benchmarks, Office31 and MNIST to USPS datasets.Comment: 7 pages, 3 figures, 3 table