Micromagnetic simulations of current-induced magnetization switching in Co/Cu/Co nanopillars

Author name used in this publication: S. Q. Shi2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Current-induced magnetization dynamics in Co/Cu/Co nanopillars

Author name used in this publication: S. Q. Shi2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Design and Analysis of the High-Order Mode Dispersion Compensating Fiber

We discussed how to design the typical trip-clad high-order mode fiber (HOMF) profiles to achieve the required dispersion properties based on LP(02) mode, to compensate all modern transmission fibers, without sacrificing other important properties, such as effective area. Finally, HOMF compensating 100km eLEAF (R) fiber has been designed. Its dispersion at 1550nm is -1217ps/nm/km, and the relative dispersion slope (RDS) is 0.02nm(-1). Only similar to 345m of HOMF is needed to achieve full dispersion and dispersion slope compensation of the span, while maintaining effective area above 52 mu m(2) over the entire C-band

Fluctuating work in coherent quantum systems: proposals and limitations

One of the most important goals in quantum thermodynamics is to demonstrate advantages of thermodynamic protocols over their classical counterparts. For that, it is necessary to (i) develop theoretical tools and experimental set-ups to deal with quantum coherence in thermodynamic contexts, and to (ii) elucidate which properties are genuinely quantum in a thermodynamic process. In this short review, we discuss proposals to define and measure work fluctuations that allow to capture quantum interference phenomena. We also discuss fundamental limitations arising due to measurement back-action, as well as connections between work distributions and quantum contextuality. We hope the different results summarised here motivate further research on the role of quantum phenomena in thermodynamics.Comment: As a chapter of: F. Binder, L. A. Correa, C. Gogolin, J. Anders, and G. Adesso (eds.), "Thermodynamics in the quantum regime - Recent Progress and Outlook", (Springer International Publishing). Second version: Misspell in the title correcte

Surface plasmon-enhanced electroluminescence in organic light-emitting diodes incorporating Au nanoparticles

Surface plasmon-enhanced electroluminescence (EL) in an organic light-emitting diode is demonstrated by incorporating the synthesized Au nanoparticles (NPs) in the hole injection layer of poly(3,4-ethylene dioxythiophene):polystyrene sulfonic acid. An increase of ∼25% in the EL intensity and efficiency are achieved for devices with Au NPs, whereas the spectral and electrical properties remain almost identical to the control device. Time-resolved photoluminescence spectroscopy reveals that the EL enhancement is ascribed to the increase in spontaneous emission rate due to the plasmonic near-field effect induced by Au NPs. © 2012 American Institute of Physics

Forecasting future Humphrey Visual Fields using deep learning

Purpose To determine if deep learning networks could be trained to forecast future 24–2 Humphrey Visual Fields (HVFs). Methods All data points from consecutive 24–2 HVFs from 1998 to 2018 were extracted from a university database. Ten-fold cross validation with a held out test set was used to develop the three main phases of model development: model architecture selection, dataset combination selection, and time-interval model training with transfer learning, to train a deep learning artificial neural network capable of generating a point-wise visual field prediction. The pointwise mean absolute error (PMAE) and difference in Mean Deviation (MD) between predicted and actual future HVF were calculated. Results More than 1.7 million perimetry points were extracted to the hundredth decibel from 32,443 24–2 HVFs. The best performing model with 20 million trainable parameters, CascadeNet- 5, was selected. The overall point-wise PMAE for the test set was 2.47 dB (95% CI: 2.45 dB to 2.48 dB), and deep learning showed a statistically significant improvement over linear models. The 100 fully trained models successfully predicted future HVFs in glaucomatous eyes up to 5.5 years in the future with a correlation of 0.92 between the MD of predicted and actual future HVF and an average difference of 0.41 dB. Conclusions Using unfiltered real-world datasets, deep learning networks show the ability to not only learn spatio-temporal HVF changes but also to generate predictions for future HVFs up to 5.5 years, given only a single HVF

MAGE-A cancer/testis antigens inhibit MDM2 ubiquitylation function and promote increased levels of MDM4

Melanoma antigen A (MAGE-A) proteins comprise a structurally and biochemically similar sub-family of Cancer/Testis antigens that are expressed in many cancer types and are thought to contribute actively to malignancy. MAGE-A proteins are established regulators of certain cancer-associated transcription factors, including p53, and are activators of several RING finger-dependent ubiquitin E3 ligases. Here, we show that MAGE-A2 associates with MDM2, a ubiquitin E3 ligase that mediates ubiquitylation of more than 20 substrates including mainly p53, MDM2 itself, and MDM4, a potent p53 inhibitor and MDM2 partner that is structurally related to MDM2. We find that MAGE-A2 interacts with MDM2 via the N-terminal p53-binding pocket and the RING finger domain of MDM2 that is required for homo/hetero-dimerization and for E2 ligase interaction. Consistent with these data, we show that MAGE-A2 is a potent inhibitor of the E3 ubiquitin ligase activity of MDM2, yet it does not have any significant effect on p53 turnover mediated by MDM2. Strikingly, however, increased MAGE-A2 expression leads to reduced ubiquitylation and increased levels of MDM4. Similarly, silencing of endogenous MAGE-A expression diminishes MDM4 levels in a manner that can be rescued by the proteasomal inhibitor, bortezomid, and permits increased MDM2/MDM4 association. These data suggest that MAGE-A proteins can: (i) uncouple the ubiquitin ligase and degradation functions of MDM2; (ii) act as potent inhibitors of E3 ligase function; and (iii) regulate the turnover of MDM4. We also find an association between the presence of MAGE-A and increased MDM4 levels in primary breast cancer, suggesting that MAGE-A-dependent control of MDM4 levels has relevance to cancer clinically

Genomic analysis of the function of the transcription factor gata3 during development of the Mammalian inner ear

We have studied the function of the zinc finger transcription factor gata3 in auditory system development by analysing temporal profiles of gene expression during differentiation of conditionally immortal cell lines derived to model specific auditory cell types and developmental stages. We tested and applied a novel probabilistic method called the gamma Model for Oligonucleotide Signals to analyse hybridization signals from Affymetrix oligonucleotide arrays. Expression levels estimated by this method correlated closely (p<0.0001) across a 10-fold range with those measured by quantitative RT-PCR for a sample of 61 different genes. In an unbiased list of 26 genes whose temporal profiles clustered most closely with that of gata3 in all cell lines, 10 were linked to Insulin-like Growth Factor signalling, including the serine/threonine kinase Akt/PKB. Knock-down of gata3 in vitro was associated with a decrease in expression of genes linked to IGF-signalling, including IGF1, IGF2 and several IGF-binding proteins. It also led to a small decrease in protein levels of the serine-threonine kinase Akt2/PKB beta, a dramatic increase in Akt1/PKB alpha protein and relocation of Akt1/PKB alpha from the nucleus to the cytoplasm. The cyclin-dependent kinase inhibitor p27(kip1), a known target of PKB/Akt, simultaneously decreased. In heterozygous gata3 null mice the expression of gata3 correlated with high levels of activated Akt/PKB. This functional relationship could explain the diverse function of gata3 during development, the hearing loss associated with gata3 heterozygous null mice and the broader symptoms of human patients with Hearing-Deafness-Renal anomaly syndrome

miRMaid: a unified programming interface for microRNA data resources

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are endogenous small RNAs that play a key role in post-transcriptional regulation of gene expression in animals and plants. The number of known miRNAs has increased rapidly over the years. The current release (version 14.0) of miRBase, the central online repository for miRNA annotation, comprises over 10.000 miRNA precursors from 115 different species. Furthermore, a large number of decentralized online resources are now available, each contributing with important miRNA annotation and information.</p> <p>Results</p> <p>We have developed a software framework, designated here as miRMaid, with the goal of integrating miRNA data resources in a uniform web service interface that can be accessed and queried by researchers and, most importantly, by computers. miRMaid is built around data from miRBase and is designed to follow the official miRBase data releases. It exposes miRBase data as inter-connected web services. Third-party miRNA data resources can be modularly integrated as miRMaid plugins or they can loosely couple with miRMaid as individual entities in the World Wide Web. miRMaid is available as a public web service but is also easily installed as a local application. The software framework is freely available under the LGPL open source license for academic and commercial use.</p> <p>Conclusion</p> <p>miRMaid is an intuitive and modular software platform designed to unify miRBase and independent miRNA data resources. It enables miRNA researchers to computationally address complex questions involving the multitude of miRNA data resources. Furthermore, miRMaid constitutes a basic framework for further programming in which microRNA-interested bioinformaticians can readily develop their own tools and data sources.</p