Picosecond optospintronic tunnel junctions

Perpendicular magnetic tunnel junctions (p-MTJs), as building blocks of spintronic devices, offer substantial potential for next-generation nonvolatile memory applications. However, their performance is fundamentally hindered by a subnanosecond speed limitation, due to spin-polarized-current-based mechanisms. Here, we report an optospintronic tunnel junction (OTJ) device with a picosecond switching speed, ultralow power, high magnetoresistance ratio, high thermal stability, and nonvolatility. This device incorporates an all-optically switchable Gd/Co bilayer coupled to a CoFeB/MgO-based p-MTJ, by subtle tuning of Ruderman–Kittel–Kasuya–Yosida interaction. An all-optical “writing” of the OTJ within 10 ps is experimentally demonstrated by time-resolved measurements. The device shows a reliable resistance “readout” with a relatively high tunnel magnetoresistance of 34.7%, as well as promising scaling toward the nanoscale with ultralow power consumption (<100 fJ for a 50-nm-sized bit). Our proof-of-concept demonstration of OTJ might ultimately pave the way toward a new category of integrated spintronic–photonic memory devices

Loss of Trop2 causes ErbB3 activation through a neuregulin-1-dependent mechanism in the mesenchymal subtype of HNSCC

In head and neck squamous cell cancer (HNSCC), four intrinsic subtypes (or groups) have been identified, and each one possesses a unique biology that will require specific treatment strategies. We previously reported that mesenchymal (group 2) tumors exhibit reduced levels of Trop2 expression. In this study, we investigated the functional role of Trop2 in HNSCC and find that loss results in autocrine activation of the EGFR family member ErbB3 via neuregulin-1. Trop2 localizes to both the cell surface and cytosol of HNSCC cells and forms a complex with neuregulin-1, which is predominantly cytosolic. Inactivation of Trop2 increases the concentration of neuregulin-1 at the cell surface where it is cleaved to activate ErbB3. In primary HNSCC, detection of ErbB3 activation was limited to Trop2 negative tumors. An analysis of the Cancer Genome Atlas (TCGA) HNSCC dataset confirms enrichment for ErbB3 activity in mesenchymal tumors. Notably, Trop2 loss triggers sensitivity to anti-ErbB3 antibodies, which results in reduced proliferation and tumorigenic growth of Trop2 negative HNSCC cancer cells. These results uncover a molecular mechanism by which tumor cells control the amount of cell-surface neuregulin-1 available for cleavage and ErbB3 activation. Moreover, we demonstrate that Trop2 is a potential surrogate biomarker to identify tumors with ErbB3 activation and may therefore respond to anti-ErbB3 therapeutics

DS-KCF: a real-time tracker for RGB-D data

© 2016 The Author(s) We propose an RGB-D single-object tracker, built upon the extremely fast RGB-only KCF tracker that is able to exploit depth information to handle scale changes, occlusions, and shape changes. Despite the computational demands of the extra functionalities, we still achieve real-time performance rates of 35–43 fps in MATLAB and 187 fps in our C++ implementation. Our proposed method includes fast depth-based target object segmentation that enables, (1) efficient scale change handling within the KCF core functionality in the Fourier domain, (2) the detection of occlusions by temporal analysis of the target’s depth distribution, and (3) the estimation of a target’s change of shape through the temporal evolution of its segmented silhouette allows. Finally, we provide an in-depth analysis of the factors affecting the throughput and precision of our proposed tracker and perform extensive comparative analysis. Both the MATLAB and C++ versions of our software are available in the public domain

Constitutively Active Canonical NF-κB Pathway Induces Severe Bone Loss in Mice

Physiologic osteoclastogenesis entails activation of multiple signal transduction pathways distal to the cell membrane receptor RANK. However, atypical osteoclastogenesis driven by pro-inflammatory stimuli has been described. We have reported recently a novel mechanism whereby endogenous mutational activation of the classical NF-κB pathway is sufficient to induce RANKL/RANK-independent osteoclastogenesis. Here we investigate the physiologic relevance of this phenomenon in vivo. Using a knock-in approach, the active form of IKK2, namely IKK2SSEE, was introduced into the myeloid lineage with the aid of CD11b-cre mice. Phenotypic assessment revealed that expression of IKK2SSEE in the myeloid compartment induced significant bone loss in vivo. This observation was supported by a dramatic increase in the number and size of osteoclasts in trabecular regions, elevated levels of circulating TRACP-5b, and reduced bone volume. Mechanistically, we observed that IKK2SSEE induced high expression of not only p65 but also p52 and RelB; the latter two molecules are considered exclusive members of the alternative NF-κB pathway. Intriguingly, RelB and P52 were both required to mediate the osteoclastogenic effect of IKK2SSEE and co-expression of these two proteins was sufficient to recapitulate osteoclastogenesis in the absence of RANKL or IKK2SSEE. Furthermore, we found that NF-κB2/p100 is a potent inhibitor of IKK2SSEE-induced osteoclastogenesis. Deletion of p52 enabled more robust osteoclast formation by the active kinase. In summary, molecular activation of IKK2 may play a role in conditions of pathologic bone destruction, which may be refractory to therapeutic interventions targeting the proximal RANKL/RANK signal

Real-Time Multi-Scale Parallel Compressive Tracking

[[abstract]]Robust visual tracking is a challenging problem because the appearance of a target may rapidly change due to significant variations in the object’s motion and the surrounding illumination. In this paper, a novel robust visual tracking algorithm is proposed based on an existing compressive tracking method. The proposed algorithm adopts multiple naive Bayes classifiers, each trained under a different scale condition, to realize online parallel multi-scale classification. Further, each classifier was initialized by randomly generating different types of Haar-like features. By doing so, the robustness of the feature classification can be improved to obtain more accurate tracking results. To enhance the real-time performance of the visual tracking system, the formula of the naive Bayes classifier is studied and simplified to speed up the processing speed of parallel multi-scale feature classification. After acceleration via formula simplification and parallel implementation, the proposed visual tracking algorithm can reach a tracking performance of approximately 45 frames per second (fps) when dealing with images of 642 × 352 pixels on a popular Intel Core i5-3230M platform. The experimental results show that the proposed algorithm outperforms state-of-the-art visual tracking methods on challenging videos in terms of success rate, tracking accuracy, and visual comparison.[[notice]]補正完