On-the-fly decoding luminescence lifetimes in the microsecond region for lanthanide-encoded suspension arrays

Significant multiplexing capacity of optical time-domain coding has been recently demonstrated by tuning luminescence lifetimes of the upconversion nanoparticles called 'τ-Dots'. It provides a large dynamic range of lifetimes from microseconds to milliseconds, which allows creating large libraries of nanotags/microcarriers. However, a robust approach is required to rapidly and accurately measure the luminescence lifetimes from the relatively slow-decaying signals. Here we show a fast algorithm suitable for the microsecond region with precision closely approaching the theoretical limit and compatible with the rapid scanning cytometry technique.We exploit this approach to further extend optical time-domain multiplexing to the downconversion luminescence, using luminescence microspheres wherein lifetimes are tuned through luminescence resonance energy transfer.We demonstrate real-time discrimination of these microspheres in the rapid scanning cytometry, and apply them to the multiplexed probing of pathogen DNA strands. Our results indicate that tunable luminescence lifetimes have considerable potential in high-throughput analytical sciences. © 2014 Macmillan Publishers Limited. All rights reserved

The Physical Basis for Long-lived Electronic Coherence in Photosynthetic Light Harvesting Systems

The physical basis for observed long-lived electronic coherence in photosynthetic light-harvesting systems is identified using an analytically soluble model. Three physical features are found to be responsible for their long coherence lifetimes: i) the small energy gap between excitonic states, ii) the small ratio of the energy gap to the coupling between excitonic states, and iii) the fact that the molecular characteristics place the system in an effective low temperature regime, even at ambient conditions. Using this approach, we obtain decoherence times for a dimer model with FMO parameters of $\approx$ 160 fs at 77 K and $\approx$ 80 fs at 277 K. As such, significant oscillations are found to persist for 600 fs and 300 fs, respectively, in accord with the experiment and with previous computations. Similar good agreement is found for PC645 at room temperature, with oscillations persisting for 400 fs. The analytic expressions obtained provide direct insight into the parameter dependence of the decoherence time scales.Comment: 5 figures; J. Phys. Chem. Lett. (2011

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response

Using random forest and decision tree models for a new vehicle prediction approach in computational toxicology

yesDrug vehicles are chemical carriers that provide beneficial aid to the drugs they bear. Taking advantage of their favourable properties can potentially allow the safer use of drugs that are considered highly toxic. A means for vehicle selection without experimental trial would therefore be of benefit in saving time and money for the industry. Although machine learning is increasingly used in predictive toxicology, to our knowledge there is no reported work in using machine learning techniques to model drug-vehicle relationships for vehicle selection to minimise toxicity. In this paper we demonstrate the use of data mining and machine learning techniques to process, extract and build models based on classifiers (decision trees and random forests) that allow us to predict which vehicle would be most suited to reduce a drug’s toxicity. Using data acquired from the National Institute of Health’s (NIH) Developmental Therapeutics Program (DTP) we propose a methodology using an area under a curve (AUC) approach that allows us to distinguish which vehicle provides the best toxicity profile for a drug and build classification models based on this knowledge. Our results show that we can achieve prediction accuracies of 80 % using random forest models whilst the decision tree models produce accuracies in the 70 % region. We consider our methodology widely applicable within the scientific domain and beyond for comprehensively building classification models for the comparison of functional relationships between two variables

eNOS Protects from Atherosclerosis Despite Relevant Superoxide Production by the Enzyme in apoE−/− Mice

All three nitric oxide synthase (NOS) isoforms are expressed in atherosclerotic plaques. NOS enzymes in general catalyse NO production. However, under conditions of substrate and cofactor deficiency, the enzyme directly catalyse superoxide formation. Considering this alternative chemistry, the effects of NOS on key events in spontaneous hyperlipidemia driven atherosclerosis have not been investigated yet. Here, we evaluate how endothelial nitric oxide synthase (eNOS) modulates leukocyte/endothelial- (L/E) and platelet/endothelial- (P/E) interactions in atherosclerosis and the production of nitric oxide (NO) and superoxide by the enzyme. Intravital microscopy (IVM) of carotid arteries revealed significantly increased L/E-interactions in apolipoproteinE/eNOS double knockout mice (apoE(-/-)/eNOS(-/-)), while P/E-interactions did not differ, compared to apoE(-/-). eNOS deficiency increased macrophage infiltration in carotid arteries and vascular cell adhesion molecule-1 (VCAM-1) expression, both in endothelial and smooth muscle cells. Despite the expression of other NOS isoforms (inducible NOS, iNOS and neuronal NOS, nNOS) in plaques, Electron Spin Resonance (ESR) measurements of NO showed significant contribution of eNOS to total circulating and vascular wall NO production. Pharmacological inhibition and genetic deletion of eNOS reduced vascular superoxide production, indicating uncoupling of the enzyme in apoE(-/-) vessels. Overt plaque formation, increased vascular inflammation and L/E- interactions are associated with significant reduction of superoxide production in apoE(-/-)/eNOS(-/-) vessels. Therefore, lack of eNOS does not cause an automatic increase in oxidative stress. Uncoupling of eNOS occurs in apoE(-/-) atherosclerosis but does not negate the enzyme's strong protective effects

Measurement of the Atmospheric Muon Spectrum from 20 to 3000 GeV

The absolute muon flux between 20 GeV and 3000 GeV is measured with the L3 magnetic muon spectrometer for zenith angles ranging from 0 degree to 58 degree. Due to the large exposure of about 150 m2 sr d, and the excellent momentum resolution of the L3 muon chambers, a precision of 2.3 % at 150 GeV in the vertical direction is achieved. The ratio of positive to negative muons is studied between 20 GeV and 500 GeV, and the average vertical muon charge ratio is found to be 1.285 +- 0.003 (stat.) +- 0.019 (syst.).Comment: Total 32 pages, 9Figure

Nucleation and crystallization in bio-based immiscible polyester blends

Bio-based thermoplastic polyesters are highly promising materials as they combine interesting thermal and physical properties and in many cases biodegradability. However, sometimes the best property balance can only be achieved by blending in order to improve barrier properties, biodegradability or mechanical properties. Nucleation, crystallization and morphology are key factors that can dominate all these properties in crystallizable biobased polyesters. Therefore, their understanding, prediction and tailoring is essential. In this work, after a brief introduction about immiscible polymer blends, we summarize the crystallization behavior of the most important bio-based (and immiscible) polyester blends, considering examples of double-crystalline components. Even though in some specific blends (e.g., polylactide/polycaprolactone) many efforts have been made to understand the influence of blending on the nucleation, crystallization and morphology of the parent components, there are still many points that have yet to be understood. In the case of other immiscible polyester blends systems, the literature is scarce, opening up opportunities in this environmentally important research topic.The authors would like to acknowledge funding by the BIODEST project ((RISE) H2020-MSCA-RISE-2017-778092

Measurement of the Shadowing of High-Energy Cosmic Rays by the Moon: A Search for TeV-Energy Antiprotons

The shadowing of high-energy cosmic rays by the Moon has been observed with a significance of 9.4 standard deviations with the L3+C muon spectrometer at CERN. A significant effect of the Earth magnetic field is observed. Since no event deficit on the east side of the Moon has been observed, an upper limit at 90% confidence level on the antiproton to proton ratio of 0.11 is obtained for primary energies around 1 TeV

A search for flaring Very-High-Energy cosmic-ray sources with the L3+C muon spectrometer

The L3+C muon detector at the Cern electron-position collider, LEP, is used for the detection of very-high-energy cosmic \gamma-ray sources through the observation of muons of energies above 20, 30, 50 and 100 GeV. Daily or monthly excesses in the rate of single-muon events pointing to some particular direction in the sky are searched for. The periods from mid July to November 1999, and April to November 2000 are considered. Special attention is also given to a selection of known \gamma-ray sources. No statistically significant excess is observed for any direction or any particular source