HIV infection of dendritic cells subverts the IFN induction pathway via IRF-1 and inhibits type 1 IFN production

Many viruses have developed mechanisms to evade the IFN response. Here, HIV-1 was shown to induce a distinct subset of IFN-stimulated genes (ISGs) in monocyte-derived dendritic cells (DCs), without detectable type I or II IFN. These ISGs all contained an IFN regulatory factor 1 (IRF-1) binding site in their promoters, and their expression was shown to be driven by IRF-1, indicating this subset was induced directly by viral infection by IRF-1. IRF-1 and -7 protein expression was enriched in HIV p24 antigen-positive DCs. A HIV deletion mutant with the IRF-1 binding site deleted from the long terminal repeat showed reduced growth kinetics. Early and persistent induction of IRF-1 was coupled with sequential transient up-regulation of its 2 inhibitors, IRF-8, followed by IRF-2, suggesting a mechanism for IFN inhibition. HIV-1 mutants with Vpr deleted induced IFN, showing that Vpr is inhibitory. However, HIV IFN inhibition was mediated by failure of IRF-3 activation rather than by its degradation, as in T cells. In contrast, herpes simplex virus type 2 markedly induced IFNβ and a broader range of ISGs to higher levels, supporting the hypothesis that HIV-1 specifically manipulates the induction of IFN and ISGs to enhance its noncytopathic replication in DCs.

Crystallographic features during martensitic transformation in Ni-Mn-Ga ferromagnetic shape memory alloys

The martensitic transformation crystallography in two Ni ₅₃Mn₂₅Ga₂₂ (at. %) ferromagnetic shape memory alloys (FSMAs) was investigated by means of misorientation calculation and pole figure analysis based on the orientation of the martensitic lamellae obtained from electron backscattered diffraction (EBSD) measurements. In the alloy that was first annealed at 1073K for 4h, and then cooled to 473K at ~4K/min and held for 30min, followed by cooling to room temperature at ~10K/min, there are only two kinds of differently orientated martensitic lamellae with a misorientation angle of ~82° distributed alternatively in each initial austenite grain. There is a compound twinning orientation relationship between the two lamellae. The prevalent orientation relationship between austenite and martensite is Kurdjumov-Sachs (K-S) relationship with (111)_A//(10I)_M, [1-10]_a//[11-1]_m. In the alloy that was annealed at 1173K for 4h followed by furnace cooling, nanoscale twins inside the martensitic lamellae were observed and the orientation relationships both between the nanotwins within one lamella and between the nanotwins in two neighboring lamellae were determined. The results presented in this paper will enrich the crystallographic data of the FSMAs and offer useful information for the development of novel FSMAs with optimal performances.

Fuzzy clustering of color and texture features for image segmentation: a study on satellite image retrieval

In this paper, a new image segmentation approach that integrates color and texture features using the fuzzy c-means clustering algorithm is described. To demonstrate the applicability of the proposed approach to satellite image retrieval, an interactive region-based image query system is designed and developed. A database comprising 400 multispectral satellite images is used to evaluate the performance of the system. The results are analyzed and discussed, and a performance comparison with other methods is included. The outcomes reveal that the proposed approach is able to improve the quality of the segmentation results as well as the retrieval performance.

Empirical investigation of multi-tier ensembles for the detection of cardiac autonomic neuropathy using subsets of the Ewing Features

This article is devoted to an empirical investigation of per- formance of several new large multi-tier ensembles for the detection of cardiac autonomic neuropathy (CAN) in diabetes patients using subsets of the Ewing features. We used new data collected by the diabetes screening research initiative (DiScRi) project, which is more than ten times larger than the data set originally used by Ewing in the investigation of CAN. The results show that new multi-tier ensembles achieved better performance compared with the outcomes published in the literature previously. The best accuracy 97.74% of the detection of CAN has been achieved by the novel multi-tier combination of AdaBoost and Bagging, where AdaBoost is used at the top tier and Bagging is used at the middle tier, for the set consisting of the following four Ewing features: the deep breathing heart rate change, the Valsalva manoeuvre heart rate change, the hand grip blood pressure change and the lying to standing blood pressure change.

Object categorization via sparse representation of local features

Sparse representation has been introduced to address many recognition problems in computer vision. In this paper, we propose a new framework for object categorization based on sparse representation of local features. Unlike most of previous sparse coding based methods in object classification that only use sparse coding to extract high-level features, the proposed method incorporates sparse representation and classification into a unified framework. Therefore, it does not need a further classifier. Experimental results show that the proposed method achieved better or comparable accuracy than the well known bag-of-features representation with various classifiers.