10,662 research outputs found
Implanted miniaturized antenna for brain computer interface applications: Analysis and design
Implantable Brain Computer Interfaces (BCIs) are designed to provide real-time control signals for prosthetic devices, study brain function, and/or restore sensory information lost as a result of injury or disease. Using Radio Frequency (RF) to wirelessly power a BCI could widely extend the number of applications and increase chronic in-vivo viability. However, due to the limited size and the electromagnetic loss of human brain tissues, implanted miniaturized antennas suffer low radiation efficiency. This work presents simulations, analysis and designs of implanted antennas for a wireless implantable RF-powered brain computer interface application. The results show that thin (on the order of 100 micrometers thickness) biocompatible insulating layers can significantly impact the antenna performance. The proper selection of the dielectric properties of the biocompatible insulating layers and the implantation position inside human brain tissues can facilitate efficient RF power reception by the implanted antenna. While the results show that the effects of the human head shape on implanted antenna performance is somewhat negligible, the constitutive properties of the brain tissues surrounding the implanted antenna can significantly impact the electrical characteristics (input impedance, and operational frequency) of the implanted antenna. Three miniaturized antenna designs are simulated and demonstrate that maximum RF power of up to 1.8 milli-Watts can be received at 2 GHz when the antenna implanted around the dura, without violating the Specific Absorption Rate (SAR) limits. © 2014 Zhao et al
Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis
We propose a novel denoising framework for task functional Magnetic Resonance
Imaging (tfMRI) data to delineate the high-resolution spatial pattern of the
brain functional connectivity via dictionary learning and sparse coding (DLSC).
In order to address the limitations of the unsupervised DLSC-based fMRI
studies, we utilize the prior knowledge of task paradigm in the learning step
to train a data-driven dictionary and to model the sparse representation. We
apply the proposed DLSC-based method to Human Connectome Project (HCP) motor
tfMRI dataset. Studies on the functional connectivity of cerebrocerebellar
circuits in somatomotor networks show that the DLSC-based denoising framework
can significantly improve the prominent connectivity patterns, in comparison to
the temporal non-local means (tNLM)-based denoising method as well as the case
without denoising, which is consistent and neuroscientifically meaningful
within motor area. The promising results show that the proposed method can
provide an important foundation for the high-resolution functional connectivity
analysis, and provide a better approach for fMRI preprocessing.Comment: 8 pages, 3 figures, MLMI201
T-cell subpopulations αβ and γδ in cord blood of very preterm infants : The influence of intrauterine infection
Open Access: This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are creditedPreterm infants are very susceptible to infections. Immune response mechanisms in this group of patients and factors that influence cord blood mononuclear cell populations remain poorly understood and are considered insufficient. However, competent immune functions of the cord blood mononuclear cells are also described. The aim of this work was to evaluate the T-cell population (CD3+) with its subpopulations bearing T-cell receptor (TCR) αβ or TCR γδ in the cord blood of preterm infants born before 32 weeks of gestation by mothers with or without an intrauterine infection. Being a pilot study, it also aimed at feasibility check and assessment of an expected effect size. The cord blood samples of 46 infants age were subjected to direct immunofluorescent staining with monoclonal antibodies and then analyzed by flow cytometry. The percentage of CD3+ cells in neonates born by mothers with diagnosis of intrauterine infection was significantly lower than in neonates born by mothers without infection (p = 0.005; Mann-Whitney U test). The number of cells did not differ between groups. Infection present in the mother did not have an influence on the TCR αβ or TCR γδ subpopulations. Our study contributes to a better understanding of preterm infants' immune mechanisms, and sets the stage for further investigations.Peer reviewedFinal Published versio
Human preferences for sexually dimorphic faces may be evolutionarily novel
This article has been made available through the Brunel Open Access Publishing Fund.A large literature proposes that preferences for exaggerated sex typicality in human faces (masculinity/femininity) reflect a long evolutionary history of sexual and social selection. This proposal implies that dimorphism was important to judgments of attractiveness and personality in ancestral environments. It is difficult to evaluate, however, because most available data come from largescale, industrialized, urban populations. Here, we report the results for 12 populations with very diverse levels of economic development. Surprisingly, preferences for exaggerated sex-specific traits are only found in the novel, highly developed environments. Similarly, perceptions that masculine males look aggressive increase strongly with development, specifically, urbanization. These data challenge the hypothesis that facial dimorphism was an important ancestral signal of heritable mate value. One possibility is that highly developed environments provide novel opportunities to discern relationships between facial traits and behavior by exposing individuals to large numbers of unfamiliar faces, revealing patterns too subtle to detect with smaller samples
Tuning a Circular p-n Junction in Graphene from Quantum Confinement to Optical Guiding
The motion of massless Dirac-electrons in graphene mimics the propagation of
photons. This makes it possible to control the charge-carriers with components
based on geometrical-optics and has led to proposals for an all-graphene
electron-optics platform. An open question arising from the possibility of
reducing the component-size to the nanometer-scale is how to access and
understand the transition from optical-transport to quantum-confinement. Here
we report on the realization of a circular p-n junction that can be
continuously tuned from the nanometer-scale, where quantum effects are
dominant, to the micrometer scale where optical-guiding takes over. We find
that in the nanometer-scale junction electrons are trapped in states that
resemble atomic-collapse at a supercritical charge. As the junction-size
increases, the transition to optical-guiding is signaled by the emergence of
whispering-gallery modes and Fabry-Perot interference. The creation of tunable
junctions that straddle the crossover between quantum-confinement and
optical-guiding, paves the way to novel design-architectures for controlling
electronic transport.Comment: 16 pages, 4 figure
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Bioavailability in soils
The consumption of locally-produced vegetables by humans may be an important exposure pathway for soil contaminants in many urban settings and for agricultural land use. Hence, prediction of metal and metalloid uptake by vegetables from contaminated soils is an important part of the Human Health Risk Assessment procedure. The behaviour of metals (cadmium, chromium, cobalt, copper, mercury, molybdenum, nickel, lead and zinc) and metalloids (arsenic, boron and selenium) in contaminated soils depends to a large extent on the intrinsic charge, valence and speciation of the contaminant ion, and soil properties such as pH, redox status and contents of clay and/or organic matter. However, chemistry and behaviour of the contaminant in soil alone cannot predict soil-to-plant transfer. Root uptake, root selectivity, ion interactions, rhizosphere processes, leaf uptake from the atmosphere, and plant partitioning are important processes that ultimately govern the accumulation ofmetals and metalloids in edible vegetable tissues. Mechanistic models to accurately describe all these processes have not yet been developed, let alone validated under field conditions. Hence, to estimate risks by vegetable consumption, empirical models have been used to correlate concentrations of metals and metalloids in contaminated soils, soil physico-chemical characteristics, and concentrations of elements in vegetable tissues. These models should only be used within the bounds of their calibration, and often need to be re-calibrated or validated using local soil and environmental conditions on a regional or site-specific basis.Mike J. McLaughlin, Erik Smolders, Fien Degryse, and Rene Rietr
SILAC-based phosphoproteomics reveals an inhibitory role of KSR1 in p53 transcriptional activity via modulation of DBC1
BACKGROUND
We have previously identified kinase suppressor of ras-1 (KSR1) as a potential regulatory gene in breast cancer. KSR1, originally described as a novel protein kinase, has a role in activation of mitogen-activated protein kinases. Emerging evidence has shown that KSR1 may have dual functions as an active kinase as well as a scaffold facilitating multiprotein complex assembly. Although efforts have been made to study the role of KSR1 in certain tumour types, its involvement in breast cancer remains unknown.
METHODS
A quantitative mass spectrometry analysis using stable isotope labelling of amino acids in cell culture (SILAC) was implemented to identify KSR1-regulated phosphoproteins in breast cancer. In vitro luciferase assays, co-immunoprecipitation as well as western blotting experiments were performed to further study the function of KSR1 in breast cancer.
RESULTS
Of significance, proteomic analysis reveals that KSR1 overexpression decreases deleted in breast cancer-1 (DBC1) phosphorylation. Furthermore, we show that KSR1 decreases the transcriptional activity of p53 by reducing the phosphorylation of DBC1, which leads to a reduced interaction of DBC1 with sirtuin-1 (SIRT1); this in turn enables SIRT1 to deacetylate p53.
CONCLUSION
Our findings integrate KSR1 into a network involving DBC1 and SIRT1, which results in the regulation of p53 acetylation and its transcriptional activity
Albumin-based cancer therapeutics for intraperitoneal drug delivery : a review
Albumin is a remarkable carrier protein with multiple cellular receptor and ligand binding sites, which are able to bind and transport numerous endogenous and exogenous compounds. The development of albumin-bound drugs is gaining increased importance in the targeted delivery of cancer therapy. Intraperitoneal (IP) drug delivery represents an attractive strategy for the local treatment of peritoneal metastasis (PM). PM is characterized by the presence of widespread metastatic tumor nodules on the peritoneum, mostly originating from gastro-intestinal or gynaecological cancers. Albumin as a carrier for chemotherapy holds considerable promise for IP delivery in patients with PM. Data from recent (pre)clinical trials suggest that IP albumin-bound chemotherapy may result in superior efficacy in the treatment of PM compared to standard chemotherapy formulations. Here, we review the evidence on albumin-bound chemotherapy with a focus on IP administration and its efficacy in PM
Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions
Improvements in sequencing technologies and reduced experimental costs have
resulted in a vast number of studies generating high-throughput data. Although
the number of methods to analyze these "omics" data has also increased,
computational complexity and lack of documentation hinder researchers from
analyzing their high-throughput data to its true potential. In this chapter we
detail our data-driven, transkingdom network (TransNet) analysis protocol to
integrate and interrogate multi-omics data. This systems biology approach has
allowed us to successfully identify important causal relationships between
different taxonomic kingdoms (e.g. mammals and microbes) using diverse types of
data
Dividend signaling: What can we learn from corporate bond responses?
© Ruoyun Lucy Zhao, 2016. The literature has reported significant abnormal returns associated with the announcements of dividend changes. Various hypotheses such as information signaling hypothesis, agency theory and wealth transfer hypothesis, have been suggested to explain the abnormal returns and volumes following the corporate stock dividend changes. The response of corporate bond, as a related security not subject to the immediate capitalization changes are used to provide evidence to help distinguish between the signaling and wealth transfer hypothesis. Corporate bonds have a significant decline in bond yields following dividend increase and a significant increase in bond yields following dividend decrease, supporting signaling hypothesis rather than wealth transfer effect
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