Morphological characterization of a human glioma cell l ine

A human malignant continuous cell line, named NG97, was recently established in our laboratory. This cell line has been serially subcultured over 100 times in standard culture media presenting no sign of cell senescence. The NG97 cell line has a doubling time of about 24 h. Immunocytochemical analysis of glial markers demonstrated that cells are positive for glial fibrillary acidic protein (GFAP) and S-100 protein, and negative for vimentin. Under phase-contrast microscope, cultures of NG97 showed cells with variable morphological features, such as small rounded cells, fusiform cells (fibroblastic-like cells), and dendritic-like cells. However, at confluence just small rounded and fusiform cells can be observed. At scanning electron microscopy (SEM) small rounded cells showed heterogeneous microextentions, including blebs and filopodia. Dendritic-like cells were flat and presented extensive prolongations, making several contacts with small rounded cells, while fusiform cells presented their surfaces dominated by microvilli. We believe that the knowledge about NG97 cell line may be useful for a deeper understanding of biological and immunological characteristics of gliomas

An Analysis of Fundamental Waffle Mode in Early AEOS Adaptive Optics Images

Adaptive optics (AO) systems have significantly improved astronomical imaging capabilities over the last decade, and are revolutionizing the kinds of science possible with 4-5m class ground-based telescopes. A thorough understanding of AO system performance at the telescope can enable new frontiers of science as observations push AO systems to their performance limits. We look at recent advances with wave front reconstruction (WFR) on the Advanced Electro-Optical System (AEOS) 3.6 m telescope to show how progress made in improving WFR can be measured directly in improved science images. We describe how a "waffle mode" wave front error (which is not sensed by a Fried geometry Shack-Hartmann wave front sensor) affects the AO point-spread function (PSF). We model details of AEOS AO to simulate a PSF which matches the actual AO PSF in the I-band, and show that while the older observed AEOS PSF contained several times more waffle error than expected, improved WFR techniques noticeably improve AEOS AO performance. We estimate the impact of these improved WFRs on H-band imaging at AEOS, chosen based on the optimization of the Lyot Project near-infrared coronagraph at this bandpass.Comment: 15 pages, 11 figures, 1 table; to appear in PASP, August 200

Prism matching for piston segmentation correction with adaptive optics systems on extremely large telescopes

Images observed at ground-based telescopes are blurred by Earth’s atmosphere. Adaptive optics systems can correct for this blurring by using a wavefront sensor to measure the instantaneous wavefront aberration created by the atmosphere, and a deformable mirror to apply correction to the aberrated wavefront. The European Extremely Large Telescope, one of the next generation of telescopes currently under construction, will have large supporting struts or arms (spiders) for the secondary mirror that obscure whole rows and columns of subapertures in the wavefront sensor. This phase discontinuity can allow large segment piston errors to arise between neighbouring segments, because the deformable mirror can produce the segment modes but the wavefront sensor senses them poorly. The spider for the EELT will have six arms, and we propose in this paper employing a six-sided prism for the wavefront sensor instead of the traditional four sided pyramid. We show that when the diffraction spikes from the spider arms are aligned in the middle of the prism faces, the sensitivty of the sensor, as measured by the sum of the singular values of the interaction matrix for the six segment piston modes, is 15% larger than if the diffraction spikes are aligned with the prism edges

Low-level Laser Therapy to the Mouse Femur Enhances the Fungicidal Response of Neutrophils against Paracoccidioides brasiliensis

Neutrophils (PMN) play a central role in host defense against the neglected fungal infection paracoccidioidomycosis (PCM), which is caused by the dimorphic fungus Paracoccidioides brasiliensis (Pb). PCM is of major importance, especially in Latin America, and its treatment relies on the use of antifungal drugs. However, the course of treatment is lengthy, leading to side effects and even development of fungal resistance. the goal of the study was to use low-level laser therapy (LLLT) to stimulate PMN to fight Pb in vivo. Swiss mice with subcutaneous air pouches were inoculated with a virulent strain of Pb or fungal cell wall components (Zymosan), and then received LLLT (780 nm; 50 mW; 12.5 J/cm2; 30 seconds per point, giving a total energy of 0.5 J per point) on alternate days at two points on each hind leg. the aim was to reach the bone marrow in the femur with light. Non-irradiated animals were used as controls. the number and viability of the PMN that migrated to the inoculation site was assessed, as well as their ability to synthesize proteins, produce reactive oxygen species (ROS) and their fungicidal activity. the highly pure PMN populations obtained after 10 days of infection were also subsequently cultured in the presence of Pb for trials of protein production, evaluation of mitochondrial activity, ROS production and quantification of viable fungi growth. PMN from mice that received LLLT were more active metabolically, had higher fungicidal activity against Pb in vivo and also in vitro. the kinetics of neutrophil protein production also correlated with a more activated state. LLLT may be a safe and non-invasive approach to deal with PCM infection.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)National Institute of Health (US NIH)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fed Univ Alfenas UNIFAL MG, Inst Biomed Sci, Dept Microbiol & Immunol, Alfenas, MG, BrazilFed Univ Alfenas UNIFAL MG, Inst Biomed Sci, Dept Biochem, Alfenas, MG, BrazilState Univ Campinas UNICAMP, Inst Biol, Dept Struct & Funct Biol, São Paulo, BrazilFed Univ São Paulo UNIFESP, Dept Microbiol Immunol & Parasitol, São Paulo, SP, BrazilMassachusetts Gen Hosp, Wellman Ctr Photomed, Boston, MA 02114 USAHarvard Univ, Sch Med, Dept Dermatol, Boston, MA 02115 USAMIT, Harvard Mit Div Hlth Sci & Technol, Cambridge, MA 02139 USAFed Univ Alfenas UNIFAL MG, Inst Biomed Sci, Dept Pathol & Parasitol, Alfenas, MG, BrazilFed Univ São Paulo UNIFESP, Dept Microbiol Immunol & Parasitol, São Paulo, SP, BrazilCNPq: 486135/2012-8CNPq: 304827/2012-6FAPEMIG: CBB-PPM-00119-14National Institute of Health (US NIH): R01AI050875CAPES: AEX-9765-14-0Web of Scienc

Toward on-sky adaptive optics control using reinforcement learning Model-based policy optimization for adaptive optics

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3-5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5-10 s, and the inference time is sufficiently small (Peer reviewe

Toward on-sky adaptive optics control using reinforcement learning Model-based policy optimization for adaptive optics

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3-5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5-10 s, and the inference time is sufficiently small (Peer reviewe

Data processing on simulated data for SHARK-NIR

A robust post processing technique is mandatory to analyse the coronagraphic high contrast imaging data. Angular Differential Imaging (ADI) and Principal Component Analysis (PCA) are the most used approaches to suppress the quasi-static structure in the Point Spread Function (PSF) in order to revealing planets at different separations from the host star. The focus of this work is to apply these two data reduction techniques to obtain the best limit detection for each coronagraphic setting that has been simulated for the SHARK-NIR, a coronagraphic camera that will be implemented at the Large Binocular Telescope (LBT). We investigated different seeing conditions ($0.4"-1"$) for stellar magnitude ranging from R=6 to R=14, with particular care in finding the best compromise between quasi-static speckle subtraction and planet detection.Comment: 9 pages, 8 figures, proceeding for the fifth Adaptive Optics for Extremely Large Telescopes (AO4ELT5) meeting in 201