The All-Sky Automated Survey for Supernovae (ASAS-SN) Light Curve Server v1.0

The All-Sky Automated Survey for Supernovae (ASAS-SN) is working towards imaging the entire visible sky every night to a depth of V~17 mag. The present data covers the sky and spans ~2-5~years with ~100-400 epochs of observation. The data should contain some ~1 million variable sources, and the ultimate goal is to have a database of these observations publicly accessible. We describe here a first step, a simple but unprecedented web interface https://asas-sn.osu.edu/ that provides an up to date aperture photometry light curve for any user-selected sky coordinate. Because the light curves are produced in real time, this web tool is relatively slow and can only be used for small samples of objects. However, it also imposes no selection bias on the part of the ASAS-SN team, allowing the user to obtain a light curve for any point on the celestial sphere. We present the tool, describe its capabilities, limitations, and known issues, and provide a few illustrative examples.Comment: 8 pages, 9 figures, submitted to PAS

Design patterns for the development of electronic health record-driven phenotype extraction algorithms

AbstractBackgroundDesign patterns, in the context of software development and ontologies, provide generalized approaches and guidance to solving commonly occurring problems, or addressing common situations typically informed by intuition, heuristics and experience. While the biomedical literature contains broad coverage of specific phenotype algorithm implementations, no work to date has attempted to generalize common approaches into design patterns, which may then be distributed to the informatics community to efficiently develop more accurate phenotype algorithms.MethodsUsing phenotyping algorithms stored in the Phenotype KnowledgeBase (PheKB), we conducted an independent iterative review to identify recurrent elements within the algorithm definitions. We extracted and generalized recurrent elements in these algorithms into candidate patterns. The authors then assessed the candidate patterns for validity by group consensus, and annotated them with attributes.ResultsA total of 24 electronic Medical Records and Genomics (eMERGE) phenotypes available in PheKB as of 1/25/2013 were downloaded and reviewed. From these, a total of 21 phenotyping patterns were identified, which are available as an online data supplement.ConclusionsRepeatable patterns within phenotyping algorithms exist, and when codified and cataloged may help to educate both experienced and novice algorithm developers. The dissemination and application of these patterns has the potential to decrease the time to develop algorithms, while improving portability and accuracy

Microgravity induces proteomics changes involved in endoplasmic reticulum stress and mitochondrial protection

On Earth, biological systems have evolved in response to environmental stressors, interactions dictated by physical forces that include gravity. The absence of gravity is an extreme stressor and the impact of its absence on biological systems is ill-defined. Astronauts who have spent extended time under conditions of minimal gravity (microgravity) experience an array of biological alterations, including perturbations in cardiovascular function. We hypothesized that physiological perturbations in cardiac function in microgravity may be a consequence of alterations in molecular and organellar dynamics within the cellular milieu of cardiomyocytes. We used a combination of mass spectrometry-based approaches to compare the relative abundance and turnover rates of 848 and 196 proteins, respectively, in rat neonatal cardiomyocytes exposed to simulated microgravity or normal gravity. Gene functional enrichment analysis of these data suggested that the protein content and function of the mitochondria, ribosomes, and endoplasmic reticulum were differentially modulated in microgravity. We confirmed experimentally that in microgravity protein synthesis was decreased while apoptosis, cell viability, and protein degradation were largely unaffected. These data support our conclusion that in microgravity cardiomyocytes attempt to maintain mitochondrial homeostasis at the expense of protein synthesis. The overall response to this stress may culminate in cardiac muscle atrophy

ASAS-SN Sky Patrol V2.0

The All-Sky Automated Survey for Supernovae (ASAS-SN) began observing in late-2011 and has been imaging the entire sky with nightly cadence since late 2017. A core goal of ASAS-SN is to release as much useful data as possible to the community. Working towards this goal, in 2017 the first ASAS-SN Sky Patrol was established as a tool for the community to obtain light curves from our data with no preselection of targets. Then, in 2020 we released static V-band photometry from 2013--2018 for 61 million sources. Here we describe the next generation ASAS-SN Sky Patrol, Version 2.0, which represents a major progression of this effort. Sky Patrol 2.0 provides continuously updated light curves for 111 million targets derived from numerous external catalogs of stars, galaxies, and solar system objects. We are generally able to serve photometry data within an hour of observation. Moreover, with a novel database architecture, the catalogs and light curves can be queried at unparalleled speed, returning thousands of light curves within seconds. Light curves can be accessed through a web interface (http://asas-sn.ifa.hawaii.edu/skypatrol/) or a Python client (https://asas-sn.ifa.hawaii.edu/documentation). The Python client can be used to retrieve up to 1 million light curves, generally limited only by bandwidth. This paper gives an updated overview of our survey, introduces the new Sky Patrol, and describes its system architecture. These results provide significant new capabilities to the community for pursuing multi-messenger and time-domain astronomy.Comment: Light curves can be accessed through a web interface http://asas-sn.ifa.hawaii.edu/skypatrol, or a Python client at http://asas-sn.ifa.hawaii.edu/documentatio