Tyrosine phosphorylation of cortactin by the FAK-Src complex at focal adhesions regulates cell motility.

BackgroundCell migration plays an important role in many physiological and pathological processes, including immune cell chemotaxis and cancer metastasis. It is a coordinated process that involves dynamic changes in the actin cytoskeleton and its interplay with focal adhesions. At the leading edge of a migrating cell, it is the re-arrangement of actin and its attachment to focal adhesions that generates the driving force necessary for movement. However, the mechanisms involved in the attachment of actin filaments to focal adhesions are still not fully understood.ResultsSignaling by the FAK-Src complex plays a crucial role in regulating the formation of protein complexes at focal adhesions to which the actin filaments are attached. Cortactin, an F-actin associated protein and a substrate of Src kinase, was found to interact with FAK through its SH3 domain and the C-terminal proline-rich regions of FAK. We found that the autophosphorylation of Tyr(397) in FAK, which is necessary for FAK activation, was not required for the interaction with cortactin, but was essential for the tyrosine phosphorylation of the associated cortactin. At focal adhesions, cortactin was phosphorylated at tyrosine residues known to be phosphorylated by Src. The tyrosine phosphorylation of cortactin and its ability to associate with the actin cytoskeleton were required in tandem for the regulation of cell motility. Cell motility could be inhibited by truncating the N-terminal F-actin binding domains of cortactin or by blocking tyrosine phosphorylation (Y421/466/475/482F mutation). In addition, the mutant cortactin phosphorylation mimic (Y421/466/475/482E) had a reduced ability to interact with FAK and promoted cell motility. The promotion of cell motility by the cortactin phosphorylation mimic could also be inhibited by truncating its N-terminal F-actin binding domains.ConclusionsOur results suggest that cortactin acts as a bridging molecule between actin filaments and focal adhesions. The cortactin N-terminus associates with F-actin, while its C-terminus interacts with focal adhesions. The tyrosine phosphorylation of cortactin by the FAK-Src complex modulates its interaction with FAK and increases its turnover at focal adhesions to promote cell motility

Conventional Pavements and Perpetual Pavements: A Rational and Empirical Approach

A study has been conducted to compare conventional pavements and perpetual pavements with a particular emphasis on perpetual pavements. One of the main drawbacks of conventional pavements and motivations for this work is the maintenance required for hot mix asphalt (HMA) pavements with sub-drainage systems. Perpetual pavements, as the name suggests, are designed with a long life. However, this is a relatively new concept and there are still many unknowns concerning their performance. This dissertation was written to answer some of the questions. The study examines structural response and performance of perpetual pavements. Also, deterioration and performance of perpetual pavements will be contrasted to conventional pavements. Empirical data from the National Center of Asphalt Technology (NCAT) Test Track study was obtained, analyzed and used as a basis for evaluating theoretical models. Computational models for both conventional and perpetual pavements were constructed and analyzed using the general purpose finite element analysis software ABAQUS. Geometry, materials and loading are modeled with sufficient accuracy. This research examined several types of responses of perpetual pavements. It extends the traditional criteria of pavement distress by suggesting that longitudinal strain at the surface of a pavement HMA layer as an important criterion. Shear strain was studied and it provides a reasonable explanation of some distresses in pavements. By studying the FEA results from conventional and perpetual pavements and a thorough investigation of the thickness effects, it provides some rationale on why strain at the top of thick pavements is critical. The effects of dynamic wheel loadings are presented. Finally, the effect of environment, specifically temperature and moisture, on perpetual pavements are studied

A Study of American COVID-19 News from the Perspective of Ideational Grammatical Metaphor Theory—Taking New York Times as an Example

Covid-19 has exerted a significant impact on people’s life and health. Former coronavirus-related studies are mainly done through the lens of cognitive linguistics, especially Interpersonal Grammatical Metaphor Theory. This study focuses on the ideational grammatical metaphors in American coronavirus-related news, taking New York Times as the corpus for qualitative and quantitative analysis. The study combines the current issues concerning Covid-19 with Halliday’s Ideational Grammatical Metaphor Theory. It not only updates the application of the theory but also explores the ideology hidden behind words, helping identify the reporter’s potential purpose. It is found that the distribution of different types of ideational grammatical metaphors is shown by the proportion it takes in related news and is closely associated with their ideological functions. With Ideational Grammatical Theory serving as a media, the study offers a new perspective and approach for news report study

Multi-dimensional data analytics and deep learning via tensor networks

With the booming of big data and multi-sensor technology, multi-dimensional data, known as tensors, has demonstrated promising capability in capturing multidimensional correlation via efficiently extracting the latent structures, and drawn considerable attention in multiple disciplines such as image processing, recommender system, data analytics, etc. In addition to the multi-dimensional nature of real data, artificially designed tensors, referred as layers in deep neural networks, have also been intensively investigated and achieved the state-of-the-art performance in imaging processing, speech processing, and natural language understanding. However, algorithms related with multi-dimensional data are unfortunately expensive in computation and storage, thus limiting its application when the computational resources are limited. Although tensor factorization has been proposed to reduce the dimensionality and alleviate the computational cost, the trade-off among computation, storage, and performance has not been well studied. To this end, we first investigate an efficient dimensionality reduction method using a novel Tensor Train (TT) factorization. In particular, we propose a Tensor Train Principal Component Analysis (TT-PCA) and a Tensor Train Neighborhood Preserving Embedding (TT-NPE) to project data onto a Tensor Train Subspace (TTS) and effectively extract the discriminative features from the data. Mathematical analysis and simulation demonstrate TT-PCA and TT-NPE achieve better trade-off among computation, storage, and performance than the bench-mark tensor-based dimensionality reduction approaches. We then extend the TT factorization into general Tensor Ring (TR) factorization and propose a tensor ring completion algorithm, which can utilize 10% randomly observed pixels to recover the gunshot video at an error rate of only 6.25%. Inspired by the novel trade-off between model complexity and data representation, we introduce a Tensor Ring Nets (TRN) to compress the deep neural networks significantly. Using the benchmark 28-layer WideResNet architectures, TRN is able to compress the neural network by 243× with only 2.3% degradation in Cifar10 image classification

Variation in load path in a wood structural system and a new reliability-based adjustment factor

This thesis introduces a new adjustment factor for the probability-based load and resistance factor (LRFD) design for wood structures. By investigating the empirical data of reaction forces for a wooden house built by the Forest Product Laboratory in 2001, it is found that the reaction values exhibit great variability. To explore the causes of this variability, a 3-D finite element model is built and analyzed using commercial software MSC/Nastran. It is found that differences in member geometry are a major cause of reaction variability. In examining the potential effect the reaction variability might have on the structural safety, reliability is assessed for two different types of wood products under several different situations. Finally, a new adjustment factor Ks, which accounts for the variability in load path, is obtained and validated based on structural reliability theory