Preparation of Inner Ear Sensory Hair Bundles for High Resolution Scanning Electron Microscopy

Chemical fixation techniques for preservation of sensory hair bundles in the mammalian inner ear for scanning electron microscopy (SEM) are reviewed. Fixatives employed were glutaraldehyde, glutaraldehyde-picrate, glutaraldehyde-tannic acid, glutaraldehyde-formaldehyde, glutaraldehyde followed by postfixation with osmium tetroxide and the osmium thiocarbohydrazide (OTOTO) method. Dehydration was routinely accomplished with ascending grades of acetone followed by critical point drying with liquid CO2 or fluorocarbon sublimation. Specimens other than those prepared by the OTOTO method were metal coated with gold, gold-palladium or platinum. Material was viewed at high resolution (2-3 nm) in a transmission electron microscope (TEM) fitted with a scanning system and an LaB6 filament. A few specimens, which were either coated with platinum, carbon or uncoated, were examined in a field emission SEM. We have concluded that glutaraldehyde fixation followed by critical point drying with CO2 and coating with platinum gives the best general preservation of stereocilia and their cross-links for routine high resolution SEM, but that carbon-coated or uncoated specimens offer potentially better results free from metal coating artifacts when viewed with field emission SEM. These methods have enabled us to make novel observations upon the surface detail and cross-links of stereocilia which have helped considerably in understanding the mechanical properties of hair bundles particularly in relation to sensory transduction. We have found that stereocilial surface detail and cross-links are sensitive to fixation regimes. In particular they are degraded by exposure to osmium tetroxide; they are also highly labile since deleterious changes in their appearance can be detected as early as 15 minutes following death

The Effect of Bacterial Endotoxin Upon the Morphology of the Tectorial Membrane and Stereocilia in the Guinea Pig Cochlea

Endotoxin of E coli was microperfused into scala tympani or injected into the cerebrospinal fluid in anaesthetised pigmented guinea pigs. The effects of endotoxin on the cochlea were studied using electrophysiological techniques and scanning electron microscopy. We found a drop in the amplitude of the cochlear microphonics and compound action potentials 2 to 2.5 hours after injection. There were also changes in the morphology of stereocilia and the tectorial membrane. The stereocilia lost their rigidity and the tectorial membrane appeared swollen. These effects were less severe in animals which were pretreated with dexamethasone

Biased total mass of cool core galaxy clusters by Sunyaev-Zel'dovich effect measurements

The Sunyaev Zel'dovich (SZ) effect from galaxy clusters is one of the most powerful cosmological tools for investigating the large-scale Universe. The big advantage of the SZ effect is its redshift independence, which is not the case for visible and X-ray observations. It allows us to directly estimate the cluster's total mass from the integrated comptonization parameter Y, even for distant clusters. However, not having a full knowing intra-cluster medium (ICM) physics can affect the results. By taking self-similar temperature and density profiles of the ICM into account, we studied how different ICM morphologies can affect the cluster total mass estimation. With the help of the high percentage of cool core (CC) clusters, as observed so far, the present analysis focuses on studying this class of objects. A sample of eight nearby (0.1 < z < 0.5) and high-mass (M > 10^(14) M_sun) clusters observed by Chandra was considered. We simulated SZ observations of these clusters through X-ray derived information and analyzed the mock SZ data again with the simplistic assumption of an isothermal beta-model profile for the ICM. The bias on the recovered cluster total mass using different sets of assumptions is estimated to be 50% higher in the case of hydrostatic equilibrium. Possible contributions to the total bias due to the line-of-sight integration and the considered ICM template are taken into account. The large biases on total mass recovery firmly support, if still necessary, cluster modeling based on more sophisticated universal profiles as derived by X-ray observations of local objects and hydrodynamical simulations.Comment: 11 pages, 4 figures; minor revisions. Accepted for publication in A&

The Good, the Bad, and the Ugly: Statistical quality assessment of SZ detections

International audienceWe examine three approaches to the problem of source classification in catalogues. Our goal is to determine the confidence withwhich the elements in these catalogues can be distinguished in populations on the basis of their spectral energy distribution (SED).Our analysis is based on the projection of the measurements onto a comprehensive SED model of the main signals in the consideredrange of frequencies. We first consider likelihood analysis, which is halfway between supervised and unsupervised methods. Next, weinvestigate an unsupervised clustering technique. Finally, we consider a supervised classifier based on artificial neural networks. Weillustrate the approach and results using catalogues from various surveys, such as X-rays (MCXC), optical (SDSS), and millimetric(Planck Sunyaev-Zeldovich (SZ)). We show that the results from the statistical classifications of the three methods are in very goodagreement with each other, although the supervised neural network-based classification shows better performance allowing the bestseparation into populations of reliable and unreliable sources in catalogues. The latest method was applied to the SZ sources detectedby the Planck satellite. It led to a classification assessing and thereby agreeing with the reliability assessment published in the PlanckSZ catalogue. Our method could easily be applied to catalogues from future large surveys such as SRG/eROSITA and Euclid

The good, the bad, and the ugly: Statistical quality assessment of SZ detections

We examine three approaches to the problem of source classification in catalogues. Our goal is to determine the confidence with which the elements in these catalogues can be distinguished in populations on the basis of their spectral energy distribution (SED). Our analysis is based on the projection of the measurements onto a comprehensive SED model of the main signals in the considered range of frequencies. We first consider likelihood analysis, which is halfway between supervised and unsupervised methods. Next, we investigate an unsupervised clustering technique. Finally, we consider a supervised classifier based on artificial neural networks. We illustrate the approach and results using catalogues from various surveys, such as X-rays (MCXC), optical (SDSS), and millimetric (Planck Sunyaev-Zeldovich (SZ)). We show that the results from the statistical classifications of the three methods are in very good agreement with each other, although the supervised neural network-based classification shows better performance allowing the best separation into populations of reliable and unreliable sources in catalogues. The latest method was applied to the SZ sources detected by the Planck satellite. It led to a classification assessing and thereby agreeing with the reliability assessment published in the Planck SZ catalogue. Our method could easily be applied to catalogues from future large surveys such as SRG/eROSITA and Euclid.We acknowledge the support of the French Agence Nationale de la Recherche under grant ANR-11-BD56-015. The development of Planck has been supported by: ESA; CNES and CNRS/INSU-IN2P3-INP (France); ASI, CNR, and INAF (Italy); NASA and DoE (USA); STFC and UKSA (UK); CSIC, MICINN and JA (Spain); Tekes, AoF and CSC (Finland); DLR and MPG (Germany); CSA (Canada); DTU Space (Denmark); SER/SSO (Switzerland); RCN (Norway); SFI (Ireland); FCT/MCTES (Portugal); and PRACE (EU).Peer Reviewe

Non-parametric deprojection of NIKA SZ observations: Pressure distribution in the Planck-discovered cluster PSZ1 G045.85+57.71

The determination of the thermodynamic properties of clusters of galaxies at intermediate and high redshift can bring new insights into the formation of large-scale structures. It is essential for a robust calibration of the mass-observable scaling relations and their scatter, which are key ingredients for precise cosmology using cluster statistics. Here we illustrate an application of high resolution $(< 20$ arcsec) thermal Sunyaev-Zel'dovich (tSZ) observations by probing the intracluster medium (ICM) of the \planck-discovered galaxy cluster \psz\ at redshift $z = 0.61$, using tSZ data obtained with the NIKA camera, which is a dual-band (150 and 260~GHz) instrument operated at the IRAM 30-meter telescope. We deproject jointly NIKA and \planck\ data to extract the electronic pressure distribution from the cluster core ($R \sim 0.02\, R_{500}$) to its outskirts ($R \sim 3\, R_{500}$) non-parametrically for the first time at intermediate redshift. The constraints on the resulting pressure profile allow us to reduce the relative uncertainty on the integrated Compton parameter by a factor of two compared to the \planck\ value. Combining the tSZ data and the deprojected electronic density profile from \xmm\ allows us to undertake a hydrostatic mass analysis, for which we study the impact of a spherical model assumption on the total mass estimate. We also investigate the radial temperature and entropy distributions. These data indicate that \psz\ is a massive ($M_{500} \sim 5.5 \times 10^{14}$ M$_{\odot}$) cool-core cluster. This work is part of a pilot study aiming at optimizing the treatment of the NIKA2 tSZ large program dedicated to the follow-up of SZ-discovered clusters at intermediate and high redshifts. (abridged)Comment: 16 pages, 10 figure