Texas A&M University

About: Texas A&M University is a education organization based out in College Station, Texas, United States. It is known for research contribution in the topics: Population & Finite element method. The organization has 72169 authors who have published 164372 publications receiving 5764236 citations.

MSCRAMM-mediated adherence of microorganisms to host tissues

Abstract: Microbial adhesion to host tissue is the initial critical event in the pathogenesis of most infections and, as such, is an attractive target for the development of new antimicrobial therapeutics. Specific microbial components (adhesins) mediate adherence to host tissues by participating in amazingly sophisticated interactions with host molecules. This review focuses on a class of cell surface adhesins that specifically interact with extracellular matrix components and which we have designated MSCRAMMs (microbial surface components recognizing adhesive matrix molecules). MSCRAMMs recognizing fibronectin-, fibrinogen-, collagen-, and heparin-related polysaccharides are discussed in terms of structural organization, ligand-binding structures, importance in host tissue colonization and invasion, and role as virulence factors.

Amino acids and immune function

Abstract: A deficiency of dietary protein or amino acids has long been known to impair immune function and increase the susceptibility of animals and humans to infectious disease. However, only in the past 15 years have the underlying cellular and molecular mechanisms begun to unfold. Protein malnutrition reduces concentrations of most amino acids in plasma. Findings from recent studies indicate an important role for amino acids in immune responses by regulating: (1) the activation of T lymphocytes, B lymphocytes, natural killer cells and macrophages; (2) cellular redox state, gene expression and lymphocyte proliferation; and (3) the production of antibodies, cytokines and other cytotoxic substances. Increasing evidence shows that dietary supplementation of specific amino acids to animals and humans with malnutrition and infectious disease enhances the immune status, thereby reducing morbidity and mortality. Arginine, glutamine and cysteine precursors are the best prototypes. Because of a negative impact of imbalance and antagonism among amino acids on nutrient intake and utilisation, care should be exercised in developing effective strategies of enteral or parenteral provision for maximum health benefits. Such measures should be based on knowledge about the biochemistry and physiology of amino acids, their roles in immune responses, nutritional and pathological states of individuals and expected treatment outcomes. New knowledge about the metabolism of amino acids in leucocytes is critical for the development of effective means to prevent and treat immunodeficient diseases. These nutrients hold great promise in improving health and preventing infectious diseases in animals and humans.

Coherent dynamics of coupled electron and nuclear spin qubits in diamond.

Abstract: Understanding and controlling the complex environment of solid-state quantum bits is a central challenge in spintronics and quantum information science. Coherent manipulation of an individual electron spin associated with a nitrogen-vacancy center in diamond was used to gain insight into its local environment. We show that this environment is effectively separated into a set of individual proximal 13 C nuclear spins, which are coupled coherently to the electron spin, and the remainder of the 13 C nuclear spins, which cause the loss of coherence. The proximal nuclear spins can be addressed and coupled individually because of quantum back-action from the electron, which modifies their energy levels and magnetic moments, effectively distinguishing them from the rest of the nuclei. These results open the door to coherent manipulation of individual isolated nuclear spins in a solid-state environment even at room temperature.

AOD-Net: All-in-One Dehazing Network

Abstract: This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net). It is designed based on a re-formulated atmospheric scattering model. Instead of estimating the transmission matrix and the atmospheric light separately as most previous models did, AOD-Net directly generates the clean image through a light-weight CNN. Such a novel end-to-end design makes it easy to embed AOD-Net into other deep models, e.g., Faster R-CNN, for improving high-level tasks on hazy images. Experimental results on both synthesized and natural hazy image datasets demonstrate our superior performance than the state-of-the-art in terms of PSNR, SSIM and the subjective visual quality. Furthermore, when concatenating AOD-Net with Faster R-CNN, we witness a large improvement of the object detection performance on hazy images.