Electrically-controllable RKKY interaction in semiconductor quantum wires

We demonstrate in theory that it is possible to all-electrically manipulate the RKKY interaction in a quasi-one-dimensional electron gas embedded in a semiconductor heterostructure, in the presence of Rashba and Dresselhaus spin-orbit interaction. In an undoped semiconductor quantum wire where intermediate excitations are gapped, the interaction becomes the short-ranged Bloembergen-Rowland super-exchange interaction. Owing to the interplay of different types of spin-orbit interaction, the interaction can be controlled to realize various spin models, e.g., isotropic and anisotropic Heisenberg-like models, Ising-like models with additional Dzyaloshinsky-Moriya terms, by tuning the external electric field and designing the crystallographic directions. Such controllable interaction forms a basis for quantum computing with localized spins and quantum matters in spin lattices.Comment: 5 pages, 1 figur

Repeatability of Corneal Elevation Maps in Keratoconus Patients Using the Tomography Matching Method

To assess repeatability of corneal tomography in successive measurements by Pentacam in keratoconus (KC) and normal eyes based on the Iterative Closest Point (ICP) algorithm. The study involved 143 keratoconic and 143 matched normal eyes. ICP algorithm was used to estimate six single and combined misalignment (CM) parameters, the root mean square (RMS) of the difference in elevation data pre (PreICP-RMS) and post (PosICP-RMS) tomography matching. Corneal keratometry, expressed in the form of M, J0 and J45 (power vector analysis parameters), was used to evaluate the effect of misalignment on corneal curvature measurements. The PreICP-RMS and PosICP-RMS were statistically higher (P < 0.01) in KC than normal eyes. CM increased significantly (p = 0.00), more in KC (16.76 ± 20.88 μm) than in normal eyes (5.43 ± 4.08 μm). PreICP-RMS, PosICP-RMS and CM were correlated with keratoconus grade (p < 0.05). Corneal astigmatism J0 was different (p = 0.01) for the second tomography measurements with misalignment consideration (−1.11 ± 2.35 D) or not (−1.18 ± 2.35 D), while M and J45 kept similar. KC corneas consistently show higher misalignments between successive tomography measurements and lower repeatability compared with healthy eyes. The influence of misalignment is evidently clearer in the estimation of astigmatism than spherical curvature. These higher errors appear correlated with KC progression

Paradoxical roles of antioxidant enzymes:Basic mechanisms and health implications

Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are generated from aerobic metabolism, as a result of accidental electron leakage as well as regulated enzymatic processes. Because ROS/RNS can induce oxidative injury and act in redox signaling, enzymes metabolizing them will inherently promote either health or disease, depending on the physiological context. It is thus misleading to consider conventionally called antioxidant enzymes to be largely, if not exclusively, health protective. Because such a notion is nonetheless common, we herein attempt to rationalize why this simplistic view should be avoided. First we give an updated summary of physiological phenotypes triggered in mouse models of overexpression or knockout of major antioxidant enzymes. Subsequently, we focus on a series of striking cases that demonstrate “paradoxical” outcomes, i.e., increased fitness upon deletion of antioxidant enzymes or disease triggered by their overexpression. We elaborate mechanisms by which these phenotypes are mediated via chemical, biological, and metabolic interactions of the antioxidant enzymes with their substrates, downstream events, and cellular context. Furthermore, we propose that novel treatments of antioxidant enzyme-related human diseases may be enabled by deliberate targeting of dual roles of the pertaining enzymes. We also discuss the potential of “antioxidant” nutrients and phytochemicals, via regulating the expression or function of antioxidant enzymes, in preventing, treating, or aggravating chronic diseases. We conclude that “paradoxical” roles of antioxidant enzymes in physiology, health, and disease derive from sophisticated molecular mechanisms of redox biology and metabolic homeostasis. Simply viewing antioxidant enzymes as always being beneficial is not only conceptually misleading but also clinically hazardous if such notions underpin medical treatment protocols based on modulation of redox pathways

Treatment of infarcted heart tissue via the capture and local delivery of circulating exosomes through antibody-conjugated magnetic nanoparticles

The systemic biodistribution of endogenous extracellular vesicles is central to the maintenance of tissue homeostasis. Here, we show that angiogenesis and heart function in infarcted heart tissue can be ameliorated by the local accumulation of exosomes collected from circulation using magnetic nanoparticles. The nanoparticles consist of a Fe3O4 core and a silica shell that is decorated with poly (ethylene glycol) conjugated through hydrazone bonds to two types of antibody, which bind either to CD63 antigens on the surface of extracellular vesicles or to myosin-light-chain surface markers on injured cardiomyocytes. On application of a local magnetic field, accumulation of the nanoparticles and cleavage of the hydrazone bonds under the acidic pH of injured cardiac tissue lead to the local release of the captured exosomes. In rabbit and rat models of myocardial infarction, the magnetic-guided accumulation of captured CD63-expressing exosomes in infarcted tissue led to reductions in infarct size as well as improved left-ventricle ejection fraction and angiogenesis. The approach could be used to manipulate endogenous exosome biodistribution for the treatment of other diseases

Depression and anxiety in relation to cancer incidence and mortality: a systematic review and meta-analysis of cohort studies

The link between depression and anxiety status and cancer outcomes has been well-documented but remains unclear. We comprehensively quantified the association between depression and anxiety defined by symptom scales or clinical diagnosis and the risk of cancer incidence, cancer-specific mortality, and all-cause mortality in cancer patients. Pooled estimates of the relative risks (RRs) for cancer incidence and mortality were performed in a meta-analysis by random effects or fixed effects models as appropriate. Associations were tested in subgroups stratified by different study and participant characteristics. Fifty-one eligible cohort studies involving 2,611,907 participants with a mean follow-up period of 10.3 years were identified. Overall, depression and anxiety were associated with a significantly increased risk of cancer incidence (adjusted RR: 1.13, 95% CI: 1.06–1.19), cancer-specific mortality (1.21, 1.16–1.26), and all-cause mortality in cancer patients (1.24, 1.13–1.35). The estimated absolute risk increases (ARIs) associated with depression and anxiety were 34.3 events/100,000 person years (15.8–50.2) for cancer incidence and 28.2 events/100,000 person years (21.5–34.9) for cancer-specific mortality. Subgroup analyses demonstrated that clinically diagnosed depression and anxiety were related to higher cancer incidence, poorer cancer survival, and higher cancer-specific mortality. Psychological distress (symptoms of depression and anxiety) was related to higher cancer-specific mortality and poorer cancer survival but not to increased cancer incidence. Site-specific analyses indicated that overall, depression and anxiety were associated with an increased incidence risks for cancers of the lung, oral cavity, prostate and skin, a higher cancer-specific mortality risk for cancers of the lung, bladder, breast, colorectum, hematopoietic system, kidney and prostate, and an increased all-cause mortality risk in lung cancer patients. These analyses suggest that depression and anxiety may have an etiologic role and prognostic impact on cancer, although there is potential reverse causality; Furthermore, there was substantial heterogeneity among the included studies, and the results should be interpreted with caution. Early detection and effective intervention of depression and anxiety in cancer patients and the general population have public health and clinical importance

Effective Lagrangian approach to vector mesons, their structure and decays∗)^{*)}

An improved update of the structure and decays of $\rho^0$, $\omega$ and $\phi$ mesons based on a chiral SU(3) Lagrangian, including anomaly terms is presented. We demonstrate that a consistent and quantitatively successful description of both pion and kaon electromagnetic form factors can be achieved. We also discuss the $e^+e^- \to \pi^+ \pi^0 \pi^-$ cross section, the Dalitz decay $\omega \to \pi^0 \mu^+ \mu^-$ and aspects of $\rho^0 \omega$ and $\omega \phi$ mixing. Relations to previous versions of the Vector Meson Dominance model will be examined.Comment: 35 pages, TeX, 14 ps figures, submitted to Z.Phys.

Modular immune-homeostatic microparticles promote immune tolerance in mouse autoimmune models

The therapeutic goal for autoimmune diseases is disease antigen-specific immune tolerance without nonspecific immune suppression. However, it is a challenge to induce antigen-specific immune tolerance in a dysregulated immune system. In this study, we developed immune-homeostatic microparticles (IHMs) that treat multiple mouse models of autoimmunity via induction of apoptosis in activated T cells and reestablishment of regulatory T cells. Specifically, in an experimental model of colitis, IHMs rapidly released monocyte chemotactic protein-1 after intravenous administration, which recruited activated T cells and then induced their apoptosis by conjugated Fas ligand on the IHM surface. This triggered professional macrophages to ingest apoptotic T cells and produce high quantities of transforming growth factor-β, which drove regulatory T cell differentiation. Furthermore, the modular design of IHMs allowed IHMs to be engineered with the autoantigen peptides that can reduce disease in an experimental autoimmune encephalomyelitis mouse model and a nonobese diabetic mouse model. This was accomplished by sustained release of the autoantigens after induction of T cell apoptosis and transforming growth factor-β production by macrophages, which promoted to establish an immune tolerant environment. Thus, IHMs may be an efficient therapeutic strategy for autoimmune diseases through induction of apoptosis and reestablishment of tolerant immune responses

Topic modeling applied to business research: A latent dirichlet allocation (LDA)-based classification for organization studies

More than 1.5 million academic documents are published each year, and this trend shows an incremental tendency for the following years. One of the main challenges for the academic community is how to organize this huge volume of documentation to have a sense of the knowledge frontier. In this study we applied Latent Dirichlet Allocation (LDA) techniques to identify primary topics in organization studies, and analyzed the relationships between academic impact and belonging to the topics detected by LDA

A deep learning approach for intelligent cockpits: learning drivers routines

Nowadays an increasing number of vehicles are being equipped with powerful cockpit systems capable of collecting drivers’ footprints over time. The collection of this valuable data opens effective opportunities for routine prediction. With the growing ability of vehicles to collect spatial and temporal information solving the routine prediction problem becomes crucial and feasible. It is then extremely important to advance and take advantage of the capabilities of these cockpit systems. A vehicle that is capable of predicting the next destination of the driver and when the driver intends to leave to that destination can prepare the journey in advance. Previous studies tackling the next location prediction problem have made use of Traditional Markov models, Neural Networks, Dynamic models, among others. In this work, a framework based on the hierarchical density-based clustering algorithm followed by a Long Short-Term Memory (LSTM) recurrent neural network is proposed for spatial-temporal prediction of drivers’ routines. Based on real-life driving scenarios of three different users, the proposed approach achieved a test set accuracy of 96.20%, 90.23%, and 86.40% when predicting the next destination and a R2 Score of 93.69, 79.21, and 28.81 when predicting the departure time, respectively. The results indicate that the proposed architecture can be implemented on the vehicle cockpit for the assistance of the management of future trips.Programme (COMPETE 2020) and national funds, through the ADI Project Bosch & UMinho “Easy Ride: Experience is everything” , ref POCI-01-0247 FEDER-039334FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020 and UIDB/00013/2020

Clinical Implication of Targeting of Cancer Stem Cells

The existence of cancer stem cells (CSCs) is receiving increasing interest particularly due to its potential ability to enter clinical routine. Rapid advances in the CSC field have provided evidence for the development of more reliable anticancer therapies in the future. CSCs typically only constitute a small fraction of the total tumor burden; however, they harbor self-renewal capacity and appear to be relatively resistant to conventional therapies. Recent therapeutic approaches aim to eliminate or differentiate CSCs or to disrupt the niches in which they reside. Better understanding of the biological characteristics of CSCs as well as improved preclinical and clinical trials targeting CSCs may revolutionize the treatment of many cancers. Copyright (c) 2012 S. Karger AG, Base