We present the first release of the MaNGA Stellar Library (MaStar), which is a large, well-calibrated, high-quality empirical library covering the wavelength range 3622-10354 Å at a resolving power of R ∼ 1800. The spectra were obtained using the same instrument as used by the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) project, by piggybacking on the Sloan Digital Sky Survey (SDSS-IV)/Apache Point Observatory Galaxy Evolution Experiment 2-N (APOGEE-2N) observations. Compared to previous empirical libraries, the MaStar library will have a higher number of stars and a more comprehensive stellar-parameter coverage, especially of cool dwarfs, low-metallicity stars, and stars with different [α/Fe], achieved by a sophisticated target-selection strategy that takes advantage of stellar-parameter catalogs from the literature. This empirical library will provide a new basis for stellar-population synthesis and is particularly well suited for stellar-population analysis of MaNGA galaxies. The first version of the library contains 8646 high-quality per-visit spectra for 3321 unique stars. Compared to photometry, the relative flux calibration of the library is accurate to 3.9% in g-r, 2.7% in r-i, and 2.2% in i-z. The data are released as part of SDSS Data Release 15. We expect the final release of the library to contain more than 10,000 stars.

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.