Hitomi (ASTRO-H) X-ray Astronomy Satellite

The Hitomi (ASTRO-H) mission is the sixth Japanese x-ray astronomy satellite developed by a large international collaboration, including Japan, USA, Canada, and Europe. The mission aimed to provide the highest energy resolution ever achieved at E  >  2  keV, using a microcalorimeter instrument, and to cover a wide energy range spanning four decades in energy from soft x-rays to gamma rays. After a successful launch on February 17, 2016, the spacecraft lost its function on March 26, 2016, but the commissioning phase for about a month provided valuable information on the onboard instruments and the spacecraft system, including astrophysical results obtained from first light observations. The paper describes the Hitomi (ASTRO-H) mission, its capabilities, the initial operation, and the instruments/spacecraft performances confirmed during the commissioning operations for about a month

Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.Peer reviewe

Visual Literacy, Knowledge Generation and the Academic Library

The organization and visual representation of knowledge as presented in academic libraries is becoming less relevant to today’s university student. With the advent of electronic databases in the 1960s continuing through the current environment where full text electronic journal content is the norm, print journal holdings are quickly becoming archive or legacy collections which are rarely used by today’s students. Basically, students rarely need to look for and retrieve physical journals from library shelves as online, full-text versions have replaced physical copies. Student library research today typically involves searching one or more electronic databases for articles usually on a particular topic or subject, identifying the relevant titles and saving the results on an electronic device or citation manager. Since the student no longer needs the journal article citation elements – that is the journal title, volume, number, year, and page number to look for and find the article itself – the citation itself is becoming irrelevant in real practical sense. It could be argued that the Digital Object Identifier (DOI) is more relevant than the citation. But also in a greater and more significant sense, because the student no longer needs to go to the physical journal collection, look for and find the journal title and see the sequential and discrete volumes and issues, the organization of published research literature is no longer visually obvious. The continuous generation of knowledge and the ongoing publication of research findings in a particular discipline as represented by the physical volumes of a particular journal are no longer visually experienced by the student. In a very real sense, the contrast between the elements of the traditional journal citation and the relatively new (implemented around 2000) DOI illustrates this point. The journal citation tells the student where that one article or piece of research fits within a broader scope and timeline while the purpose and function of the DOI is to only identify the singular object. Without the visual representation and use of the library’s physical journal collection, librarians and faculty cannot assume students intuitively understand the traditional organization and presentation of published knowledge. This subtle yet profound change should be recognized and addressed by the academy and in the curriculum

Announcing Big-Bee: An initiative to promote understanding of bees through image and trait digitization.

While bees are critical to sustaining a large proportion of global food production, as well as pollinating both wild and cultivated plants, they are decreasing in both numbers and diversity. Our understanding of the factors driving these declines is limited, in part, because we lack sufficient data on the distribution of bee species to predict changes in their geographic range under climate change scenarios. Additionally lacking is adequate data on the behavioral and anatomical traits that may make bees either vulnerable or resilient to human-induced environmental changes, such as habitat loss and climate change. Fortunately, a wealth of associated attributes can be extracted from the specimens deposited in natural history collections for over 100 years.Extending Anthophila Research Through Image and Trait Digitization (Big-Bee) is a newly funded US National Science Foundation Advancing Digitization of Biodiversity Collections project. Over the course of three years, we will create over one million high-resolution 2D and 3D images of bee specimens (Fig. 1), representing over 5,000 worldwide bee species, including most of the major pollinating species. We will also develop tools to measure bee traits from images and generate comprehensive bee trait and image datasets to measure changes through time. The Big-Bee network of participating institutions includes 13 US institutions (Fig. 2) and partnerships with US government agencies. We will develop novel mechanisms for sharing image datasets and datasets of bee traits that will be available through an open, Symbiota-Light (Gilbert et al. 2020) data portal called the Bee Library. In addition, biotic interaction and species association data will be shared via Global Biotic Interactions (Poelen et al. 2014). The Big-Bee project will engage the public in research through community science via crowdsourcing trait measurements and data transcription from images using Notes from Nature (Hill et al. 2012). Training and professional development for natural history collection staff, researchers, and university students in data science will be provided through the creation and implementation of workshops focusing on bee traits and species identification. We are also planning a short, artistic college radio segment called "the Buzz" to get people excited about bees, biodiversity, and the wonders of our natural world.This poster was prepared for TDWG 2021 virtual conference