Pulmonary vasospasm in systemic sclerosis: noninvasive techniques for detection

In a subgroup of patients with systemic sclerosis (SSc), vasospasm affecting the pulmonary circulation may contribute to worsening respiratory symptoms, including dyspnea. Noninvasive assessment of pulmonary blood flow (PBF), utilizing inert-gas rebreathing (IGR) and dual-energy computed-tomography pulmonary angiography (DE-CTPA), may be useful for identifying pulmonary vasospasm. Thirty-one participants (22 SSc patients and 9 healthy volunteers) underwent PBF assessment with IGR and DE-CTPA at baseline and after provocation with a cold-air inhalation challenge (CACh). Before the study investigations, participants were assigned to subgroups: group A included SSc patients who reported increased breathlessness after exposure to cold air (n = 11), group B included SSc patients without cold-air sensitivity (n = 11), and group C patients included the healthy volunteers. Median change in PBF from baseline was compared between groups A, B, and C after CACh. Compared with groups B and C, in group A there was a significant decline in median PBF from baseline at 10 minutes (−10%; range: −52.2% to 4.0%; P < 0.01), 20 minutes (−17.4%; −27.9% to 0.0%; P < 0.01), and 30 minutes (−8.5%; −34.4% to 2.0%; P < 0.01) after CACh. There was no significant difference in median PBF change between groups B or C at any time point and no change in pulmonary perfusion on DE-CTPA. Reduction in pulmonary blood flow following CACh suggests that pulmonary vasospasm may be present in a subgroup of patients with SSc and may contribute to worsening dyspnea on exposure to cold

Sample entropy analysis of EEG signals via artificial neural networks to model patients' consciousness level based on anesthesiologists experience.

Electroencephalogram (EEG) signals, as it can express the human brain's activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA). Bispectral (BIS) index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD) method and analyzed using sample entropy (SampEn) analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN) model through using expert assessment of consciousness level (EACL) which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.This research is supported by the Center forDynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by Ministry of Science and Technology (Grant no. MOST103-2911-I-008-001). Also, it is supported by National Chung-Shan Institute of Science & Technology in Taiwan (Grant nos. CSIST-095-V301 and CSIST-095-V302)

A note on anti-coordination and social interactions

This note confirms a conjecture of [Bramoull\'{e}, Anti-coordination and social interactions, Games and Economic Behavior, 58, 2007: 30-49]. The problem, which we name the maximum independent cut problem, is a restricted version of the MAX-CUT problem, requiring one side of the cut to be an independent set. We show that the maximum independent cut problem does not admit any polynomial time algorithm with approximation ratio better than $n^{1-\epsilon}$, where $n$ is the number of nodes, and $\epsilon$ arbitrarily small, unless P=NP. For the rather special case where each node has a degree of at most four, the problem is still MAXSNP-hard.Comment: 7 page

Direct observation of delithiation as the origin of analog memristance in LixNbO2

The discovery of analog LixNbO2 memristors revealed a promising new memristive mechanism wherein the diffusion of Li+ rather than O2- ions enables precise control of the resistive states. However, directly correlating lithium concentration with changes to the electronic structure in active layers remains a challenge and is required to truly understand the underlying physics. Chemically delithiated single crystals of LiNbO2 present a model system for correlating lithium variation with spectroscopic signatures from operando soft x-ray spectroscopy studies of device active layers. Using electronic structure modeling of the x-ray spectroscopy of LixNbO2 single crystals, we demonstrate that the intrinsic memristive behavior in LixNbO2 active layers results from field-induced degenerate p-type doping. We show that electrical operation of LixNbO2-based memristors is viable even at marginal Li deficiency and that the analog memristive switching occurs well before the system is fully metallic. This study serves as a benchmark for material synthesis and characterization of future LixNbO2-based memristor devices and suggests that valence change switching is a scalable alternative that circumvents the electroforming typically required for filamentary-based memristors

On a multi-dimensional risk model with regime switching

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Up-regulation of METCAM/MUC18 promotes motility, invasion, and tumorigenesis of human breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Conflicting research has identified METCAM/MUC18, an integral membrane cell adhesion molecule (CAM) in the Ig-like gene super-family, as both a tumor promoter and a tumor suppressor in the development of breast cancer. To resolve this, we have re-investigated the role of this CAM in the progression of human breast cancer cells.</p> <p>Methods</p> <p>Three breast cancer cell lines were used for the tests: one luminal-like breast cancer cell line, MCF7, which did not express any METCAM/MUC18, and two basal-like breast cancer cell lines, MDA-MB-231 and MDA-MB-468, which expressed moderate levels of the protein.</p> <p>MCF7 cells were transfected with the human METCAM/MUC18 cDNA to obtain G418-resistant clones which expressed the protein and were used for testing effects of human METCAM/MUC18 expression on <it>in vitro </it>motility and invasiveness, and <it>in vitro </it>and <it>in vivo </it>tumorigenesis. Both MDA-MB-231 and MDA-MB-468 cells already expressed METCAM/MUC18. They were directly used for <it>in vitro </it>tests in the presence and absence of an anti-METCAM/MUC18 antibody.</p> <p>Results</p> <p>In MCF7 cells, enforced METCAM/MUC18 expression increased <it>in vitro </it>motility, invasiveness, anchorage-independent colony formation (<it>in vitro </it>tumorigenesis), and <it>in vivo </it>tumorigenesis. In both MDA-MB-231 and MDA-MB-468 cells, the anti-METCAM/MUC18 antibody inhibited both motility and invasiveness. Though both MDA-MB-231 and MDA-MB-468 cells established a disorganized growth in 3D basement membrane culture assay, the introduction of the anti-METCAM/MUC18 antibody completely destroyed their growth in the 3D culture.</p> <p>Conclusion</p> <p>These findings support the notion that human METCAM/MUC18 expression promotes the progression of human breast cancer cells by increasing their motility, invasiveness and tumorigenesis.</p