Aspects of the Mass Distribution of Interstellar Dust Grains in the Solar System from In-Situ Measurements

The in-situ detection of interstellar dust grains in the Solar System by the dust instruments on-board the Ulysses and Galileo spacecraft as well as the recent measurements of hyperbolic radar meteors give information on the properties of the interstellar solid particle population in the solar vicinity. Especially the distribution of grain masses is indicative of growth and destruction mechanisms that govern the grain evolution in the interstellar medium. The mass of an impacting dust grain is derived from its impact velocity and the amount of plasma generated by the impact. Because the initial velocity and the dynamics of interstellar particles in the Solar System are well known, we use an approximated theoretical instead of the measured impact velocity to derive the mass of interstellar grains from the Ulysses and Galileo in-situ data. The revised mass distributions are steeper and thus contain less large grains than the ones that use measured impact velocities, but large grains still contribute significantly to the overall mass of the detected grains. The flux of interstellar grains with masses $> 10^{-14} {\rm kg}$ is determined to be $1\cdot 10^{-6} {\rm m}^{-2} {\rm s}^{-1}$. The comparison of radar data with the extrapolation of the Ulysses and Galileo mass distribution indicates that the very large ($m > 10^{-10} {\rm kg}$) hyperbolic meteoroids detected by the radar are not kinematically related to the interstellar dust population detected by the spacecraft.Comment: 14 pages, 11 figures, to appear in JG

Galileo dust data from the jovian system: 2000 to 2003

The Galileo spacecraft was orbiting Jupiter between Dec 1995 and Sep 2003. The Galileo dust detector monitored the jovian dust environment between about 2 and 370 R_J (jovian radius R_J = 71492 km). We present data from the Galileo dust instrument for the period January 2000 to September 2003. We report on the data of 5389 particles measured between 2000 and the end of the mission in 2003. The majority of the 21250 particles for which the full set of measured impact parameters (impact time, impact direction, charge rise times, charge amplitudes, etc.) was transmitted to Earth were tiny grains (about 10 nm in radius), most of them originating from Jupiter's innermost Galilean moon Io. Their impact rates frequently exceeded 10 min^-1. Surprisingly large impact rates up to 100 min^-1 occurred in Aug/Sep 2000 when Galileo was at about 280 R_J from Jupiter. This peak in dust emission appears to coincide with strong changes in the release of neutral gas from the Io torus. Strong variability in the Io dust flux was measured on timescales of days to weeks, indicating large variations in the dust release from Io or the Io torus or both on such short timescales. Galileo has detected a large number of bigger micron-sized particles mostly in the region between the Galilean moons. A surprisingly large number of such bigger grains was measured in March 2003 within a 4-day interval when Galileo was outside Jupiter's magnetosphere at approximately 350 R_J jovicentric distance. Two passages of Jupiter's gossamer rings in 2002 and 2003 provided the first actual comparison of in-situ dust data from a planetary ring with the results inferred from inverting optical images.Comment: 59 pages, 13 figures, 6 tables, submitted to Planetary and Space Scienc

Bringing Open Data to Whole Slide Imaging

Supplementary information associated with Besson et al. (2019) ECDP 2019 Faced with the need to support a growing number of whole slide imaging (WSI) file formats, our team has extended a long-standing community file format (OME-TIFF) for use in digital pathology. The format makes use of the core TIFF specification to store multi-resolution (or "pyramidal") representations of a single slide in a flexible, performant manner. Here we describe the structure of this format, its performance characteristics, as well as an open-source library support for reading and writing pyramidal OME-TIFFs

A call for public archives for biological image data

Public data archives are the backbone of modern biological and biomedical research. While archives for biological molecules and structures are well-established, resources for imaging data do not yet cover the full range of spatial and temporal scales or application domains used by the scientific community. In the last few years, the technical barriers to building such resources have been solved and the first examples of scientific outputs from public image data resources, often through linkage to existing molecular resources, have been published. Using the successes of existing biomolecular resources as a guide, we present the rationale and principles for the construction of image data archives and databases that will be the foundation of the next revolution in biological and biomedical informatics and discovery.Comment: 13 pages, 1 figur

Interstellar Dust Inside and Outside the Heliosphere

In the early 1990s, after its Jupiter flyby, the Ulysses spacecraft identified interstellar dust in the solar system. Since then the in-situ dust detector on board Ulysses continuously monitored interstellar grains with masses up to 10e-13 kg, penetrating deep into the solar system. While Ulysses measured the interstellar dust stream at high ecliptic latitudes between 3 and 5 AU, interstellar impactors were also measured with the in-situ dust detectors on board Cassini, Galileo and Helios, covering a heliocentric distance range between 0.3 and 3 AU in the ecliptic plane. The interstellar dust stream in the inner solar system is altered by the solar radiation pressure force, gravitational focussing and interaction of charged grains with the time varying interplanetary magnetic field. The grains act as tracers of the physical conditions in the local interstellar cloud (LIC). Our in-situ measurements imply the existence of a population of 'big' interstellar grains (up to 10e-13 kg) and a gas-to-dust-mass ratio in the LIC which is a factor of > 2 larger than the one derived from astronomical observations, indicating a concentration of interstellar dust in the very local interstellar medium. Until 2004, the interstellar dust flow direction measured by Ulysses was close to the mean apex of the Sun's motion through the LIC, while in 2005, the data showed a 30 deg shift, the reason of which is presently unknown. We review the results from spacecraft-based in-situ interstellar dust measurements in the solar system and their implications for the physical and chemical state of the LIC.Comment: 10 pages, 2 b/w figures, 1 colour figure; submitted to Space Science Review

Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping

To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1–2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks

Developing open-source software for bioimage analysis: opportunities and challenges

Fast-paced innovations in imaging have resulted in single systems producing exponential amounts of data to be analyzed. Computational methods developed in computer science labs have proven to be crucial for analyzing these data in an unbiased and efficient manner, reaching a prominent role in most microscopy studies. Still, their use usually requires expertise in bioimage analysis, and their accessibility for life scientists has therefore become a bottleneck.Open-source software for bioimage analysis has developed to disseminate these computational methods to a wider audience, and to life scientists in particular. In recent years, the influence of many open-source tools has grown tremendously, helping tens of thousands of life scientists in the process. As creators of successful open-source bioimage analysis software, we here discuss the motivations that can initiate development of a new tool, the common challenges faced, and the characteristics required for achieving success

TrakEM2 Software for Neural Circuit Reconstruction

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis

BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples.

Light-sheet imaging of cleared and expanded samples creates terabyte-sized datasets that consist of many unaligned three-dimensional image tiles, which must be reconstructed before analysis. We developed the BigStitcher software to address this challenge. BigStitcher enables interactive visualization, fast and precise alignment, spatially resolved quality estimation, real-time fusion and deconvolution of dual-illumination, multitile, multiview datasets. The software also compensates for optical effects, thereby improving accuracy and enabling subsequent biological analysis