Tobias Lammel, P. Boisseaux, M. Fernández-Cruz
et al.
BackgroundGraphene and graphene derivative nanoplatelets represent a new generation of nanomaterials with unique physico-chemical properties and high potential for use in composite materials and biomedical devices. To date little is known about the impact graphene nanomaterials may have on human health in the case of accidental or intentional exposure. The objective of this study was to assess the cytotoxic potential of graphene nanoplatelets with different surface chemistry towards a human hepatoma cell line, Hep G2, and identify the underlying toxicity targets.MethodsGraphene oxide (GO) and carboxyl graphene (CXYG) nanoplatelet suspensions were obtained in water and culture medium. Size frequency distribution of the suspensions was determined by means of dynamic light scattering. Height, lateral dimension and shape of the nanoplatelets were determined using atomic force and electron microscopy. Cytotoxicity of GO and CXYG nanoplatelets was assessed in Hep G2 cells using a battery of assays covering different modes of action including alterations of metabolic activity, plasma membrane integrity and lysosomal function. Induction of oxidative stress was assessed by measuring intracellular reactive oxygen species levels. Interaction with the plasma membrane, internalization and intracellular fate of GO and CXYG nanoplatelets was studied by scanning and transmission electron microscopy.ResultsSupplementing culture medium with serum was essential to obtain stable GO and CXYG suspensions. Both graphene derivatives had high affinity for the plasma membrane and caused structural damage of the latter at concentrations as low as 4 μg/ml. The nanoplatelets penetrated through the membrane into the cytosol, where they were concentrated and enclosed in vesicles. GO and CXYG accumulation in the cytosol was accompanied by an increase in intracellular reactive oxygen species (ROS) levels, alterations in cellular ultrastructure and changes in metabolic activity.ConclusionsGO and CXYG nanoplatelets caused dose- and time-dependent cytotoxicity in Hep G2 cells with plasma membrane damage and induction of oxidative stress being important modes of toxicity. Both graphene derivatives were internalized by Hep G2, a non-phagocytotic cell line. Moreover, they exerted no toxicity when applied at very low concentrations (< 4 μg/ml). GO and CXYG nanoplatelets may therefore represent an attractive material for biomedical applications.
Employing Fermi-LAT gamma ray observations, several independent groups have found excess extended gamma ray emission at the Galactic center (GC). Both, annihilating dark matter (DM) or a population of $\sim 10^3$ unresolved millisecond pulsars (MSPs) are regarded as well motivated possible explanations. However, there is significant uncertainties in the diffuse galactic background at the GC. We have performed a revaluation of these two models for the extended gamma ray source at the GC by accounting for the systematic uncertainties of the Galactic diffuse emission model. We also marginalize over point source and diffuse background parameters in the region of interest. We show that the excess emission is significantly more extended than a point source. We find that the DM (or pulsars population) signal is larger than the systematic errors and therefore proceed to determine the sectors of parameter space that provide an acceptable fit to the data. We found that a population of order a 1000 MSPs with parameters consistent with the average spectral shape of Fermi-LAT measured MSPs was able to fit the GC excess emission. For DM, we found that a pure $\tau^+\tau^-$ annihilation channel is not a good fit to the data. But a mixture of $\tau^+\tau^-$ and $b\bar{b}$ with a $\left $ of order the thermal relic value and a DM mass of around 20 to 60 GeV provides an adequate fit.
Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of many autoimmune diseases. This paper proposes an automatic framework for this classification task, by utilizing the deep convolutional neural networks (CNNs) which have recently attracted intensive attention in visual recognition. In addition to describing the proposed classification framework, this paper elaborates several interesting observations and findings obtained by our investigation. They include the important factors that impact network design and training, the role of rotation-based data augmentation for cell images, the effectiveness of cell image masks for classification, and the adaptability of the CNN-based classification system across different datasets. Extensive experimental study is conducted to verify the above findings and compares the proposed framework with the well-established image classification models in the literature. The results on benchmark datasets demonstrate that 1) the proposed framework can effectively outperform existing models by properly applying data augmentation, 2) our CNN-based framework has excellent adaptability across different datasets, which is highly desirable for cell image classification under varying laboratory settings. Our system is ranked high in the cell image classification competition hosted by ICPR 2014.
To uniformly determine the properties of supernova remnants (SNRs) at high energies, we have developed the first systematic survey at energies from 1 to 100 GeV using data from the Fermi Large Area Telescope (LAT). Based on the spatial overlap of sources detected at GeV energies with SNRs known from radio surveys, we classify 30 sources as likely GeV SNRs. We also report 14 marginal associations and 245 flux upper limits. A mock catalog in which the positions of known remnants are scrambled in Galactic longitude allows us to determine an upper limit of 22% on the number of GeV candidates falsely identified as SNRs. We have also developed a method to estimate spectral and spatial systematic errors arising from the diffuse interstellar emission model, a key component of all Galactic Fermi LAT analyses. By studying remnants uniformly in aggregate, we measure the GeV properties common to these objects and provide a crucial context for the detailed modeling of individual SNRs. Combining our GeV results with multiwavelength (MW) data, including radio, X-ray, and TeV, we demonstrate the need for improvements to previously sufficient, simple models describing the GeV and radio emission from these objects. We model the GeV and MW emission from SNRs in aggregate to constrain their maximal contribution to observed Galactic cosmic rays.
The Fermi-LAT Collaboration, M. Ackermann, M. Ajello
et al.
We search for evidence of dark matter (DM) annihilation in the isotropic gamma-ray background (IGRB) measured with 50 months of Fermi Large Area Telescope (LAT) observations. An improved theoretical description of the cosmological DM annihilation signal, based on two complementary techniques and assuming generic weakly interacting massive particle (WIMP) properties, renders more precise predictions compared to previous work. More specifically, we estimate the cosmologically-induced gamma-ray intensity to have an uncertainty of a factor ~ 20 in canonical setups. We consistently include both the Galactic and extragalactic signals under the same theoretical framework, and study the impact of the former on the IGRB spectrum derivation. We find no evidence for a DM signal and we set limits on the DM-induced isotropic gamma-ray signal. Our limits are competitive for DM particle masses up to tens of TeV and, indeed, are the strongest limits derived from Fermi LAT data at TeV energies. This is possible thanks to the new Fermi LAT IGRB measurement, which now extends up to an energy of 820 GeV. As a result, we quantify uncertainties in detail and show the potential this type of search offers for testing the WIMP paradigm with a complementary and truly cosmological probe ofmore » DM particle signals.« less
We compute the γ-ray and neutrino diffuse emission of the Galaxy on the basis of a recently proposed phenomenological model characterized by radially dependent cosmic-ray (CR) transport properties. We show how this model, designed to reproduce both Fermi-LAT γ-ray data and local CR observables, naturally reproduces the anomalous TeV diffuse emission observed by Milagro in the inner Galactic plane. Above 100 TeV our picture predicts a neutrino flux that is about five (two) times larger than the neutrino flux computed with conventional models in the Galactic Center region (full-sky). Explaining in that way up to ∼25% of the flux measured by IceCube, we reproduce the full-sky IceCube spectrum adding an extra-Galactic component derived from the muonic neutrinos flux in the northern hemisphere. We also present precise predictions for the Galactic plane region where the flux is dominated by the Galactic emission.