Study of Effector CD8+ T Cell Interactions with Cortical Neurons in Response to Inflammation in Mouse Brain Slices and Neuronal Cultures

Cytotoxic CD8+ T cells contribute to neuronal damage in inflammatory and degenerative CNS disorders, such as multiple sclerosis (MS). The mechanism of cortical damage associated with CD8+ T cells is not well understood. We developed in vitro cell culture and ex vivo brain slice co-culture models of brain inflammation to study CD8+ T cell–neuron interactions. To induce inflammation, we applied T cell conditioned media, which contains a variety of cytokines, during CD8+ T cell polyclonal activation. Release of IFNγ and TNFα from co-cultures was verified by ELISA, confirming an inflammatory response. We also visualized the physical interactions between CD8+ T cells and cortical neurons using live-cell confocal imaging. The imaging revealed that T cells reduced their migration velocity and changed their migratory patterns under inflammatory conditions. CD8+ T cells increased their dwell time at neuronal soma and dendrites in response to added cytokines. These changes were seen in both the in vitro and ex vivo models. The results confirm that these in vitro and ex vivo models provide promising platforms for the study of the molecular details of neuron–immune cell interactions under inflammatory conditions, which allow high-resolution live microscopy and are readily amenable to experimental manipulation

Local Activities of the Membranes Associated with Glycosaminoglycan-Chitosan Complexes in Bone Cells

Chitosan is a cationic polysaccharide derived from the partial deacetylation of chitin. Hyaluronic acid (HA), chondroitin sulfate (CS) and heparin (HP) are anionic glycosaminoglycans (GCGs) which can regulate osteogenic activity. In this study, chitosan membranes were prepared by glutaraldehyde crosslinking reaction and then complexed with three different types of GCGs. 7F2 osteoblasts-like cells and macrophages Raw264.7 were used as models to study the influence of chitosan membranes on osteometabolism. Although chitosan membranes are highly hydrophilic, the membranes associated with GCG-chitosan complexes showed about 60-70% cell attachment. Furthermore, the membranes associated with HP-chitosan complexes could increase ALP activity in comparison with chitosan films only. Three types of the membranes associated with GCG-chitosan complexes could significantly inhibit LPS induced-nitric oxide expression. In addition, chitosan membranes associated with HP and HA can down-regulate tartrate-resistant acid phosphatase (TRAP) activity but not CS-chitosan complexes. Based on these results, we conclude that chitosan membranes associated with HP can increase ALP activity in osteoblasts and chitosan membranes associated with HP and HA reduce TRAP activity in osteoclasts

Robust Affinity Propagation using Preference Estimation

Affinity propagation is a novel unsupervised learning algorithm for exemplar-based clustering without the priori knowledge of the number of clusters (NC). In this article, the influence of the “preference” on the accuracy of AP output is addressed. We present a robust AP clustering method, which estimates what preference value could possibly yield an optimal clustering result. To demonstrate the performance promotion, we apply the robust AP on picture clustering, using local SIFT, global MPEG-7 CLD, and the proposed preference as the input of AP. The experimental results show that over 40% enhancement of ARI accuracy for several image datasets

MAT: A Multi-strength Adversarial Training Method to Mitigate Adversarial Attacks

Some recent works revealed that deep neural networks (DNNs) are vulnerable to so-called adversarial attacks where input examples are intentionally perturbed to fool DNNs. In this work, we revisit the DNN training process that includes adversarial examples into the training dataset so as to improve DNN's resilience to adversarial attacks, namely, adversarial training. Our experiments show that different adversarial strengths, i.e., perturbation levels of adversarial examples, have different working zones to resist the attack. Based on the observation, we propose a multi-strength adversarial training method (MAT) that combines the adversarial training examples with different adversarial strengths to defend adversarial attacks. Two training structures - mixed MAT and parallel MAT - are developed to facilitate the tradeoffs between training time and memory occupation. Our results show that MAT can substantially minimize the accuracy degradation of deep learning systems to adversarial attacks on MNIST, CIFAR-10, CIFAR-100, and SVHN.Comment: 6 pages, 4 figures, 2 table

Two distinct topological phases in the mixed valence compound YbB6 and its differences from SmB6

We discuss the evolution of topological states and their orbital textures in the mixed valence compounds SmB6 and YbB6 within the framework of the generalized gradient approximation plus onsite Coulomb interaction (GGA+U) scheme for a wide range of values of U. In SmB6, the topological Kondo insulator (TKI) gap is found to be insensitive to the value of U, but in sharp contrast, Kondo physics in isostructural YbB6 displays a surprising sensitivity to U. In particular, as U is increased in YbB6, the correlated TKI state in the weak-coupling regime transforms into a d-p-type topological insulator phase with a band inversion between Yb-5d and B-2p orbitals in the intermediate coupling range, without closing the insulating energy gap throughout this process. Our theoretical predictions related to the TKI and non-TKI phases in SmB6 and YbB6 are in substantial accord with recent angle-resolved photoemission spectroscopy (ARPES) experiments.Comment: 6 pages, 4 figures URL: http://link.aps.org/doi/10.1103/PhysRevB.91.15515

Surface Versus Bulk Dirac States Tuning in a Three-Dimensional Topological Dirac Semimetal

Recently, crystalline-symmetry-protected three-dimensional (3D) bulk Dirac semimetal phase has been experimentally identified in a stoichiometric high-mobility compound, Cd3As2. The Dirac state observed in Cd3As2 has been attributed to originate mostly from the bulk state while calculations show that the bulk and surface states overlap over the entire Dirac dispersion energy range. In this study, we unambiguously reveal doping induced evolution of the ground state of surface and bulk electron dynamics in a 3D Dirac semimetal. We develop a systematic technique to isolate the surface and bulk states in Cd3As2, by simultaneously utilizing angle-resolved photoemission spectroscopy (ARPES) and in-situ surface deposition. Our experimental results provide a method for tuning the chemical potential as well as to observe surface states degenerate with bulk states, which will be useful for future applications of 3D Dirac semimetal.Comment: 5 pages, 4 figure