When companies have ties to politicians or military officials

Entrepreneurs want to reduce uncertainty and shape environments to their advantage. To do so, they sometimes collaborate with government leaders to gain valuable information, resources, and favourable legislation

Strategic silence: why are some companies not publicising their environmental certifications?

It’s for fears of accusations of greenwashing, argue Chad Carlos and Ben Lewis

Further evidence for the involvement of EFL1 in a Shwachman-Diamond-like syndrome and expansion of the phenotypic features.

Recent evidence has implicated EFL1 in a phenotype overlapping Shwachman-Diamond syndrome (SDS), with the functional interplay between EFL1 and the previously known causative gene SBDS accounting for the similarity in clinical features. Relatively little is known about the phenotypes associated with pathogenic variants in the EFL1 gene, but the initial indication was that phenotypes may be more severe, when compared with SDS. We report a pediatric patient who presented with a metaphyseal dysplasia and was found to have biallelic variants in EFL1 on reanalysis of trio whole-exome sequencing data. The variant had not been initially reported because of the research laboratory's focus on de novo variants. Subsequent phenotyping revealed variability in her manifestations. Although her metaphyseal abnormalities were more severe than in the original reported cohort with EFL1 variants, the bone marrow abnormalities were generally mild, and there was equivocal evidence for pancreatic insufficiency. Despite the limited number of reported patients, variants in EFL1 appear to cause a broader spectrum of symptoms that overlap with those seen in SDS. Our report adds to the evidence of EFL1 being associated with an SDS-like phenotype and provides information adding to our understanding of the phenotypic variability of this disorder. Our report also highlights the value of exome data reanalysis when a diagnosis is not initially apparent

Evidence for Diversity in Transcriptional Profiles of Single Hematopoietic Stem Cells

Hematopoietic stem cells replenish all the cells of the blood throughout the lifetime of an animal. Although thousands of stem cells reside in the bone marrow, only a few contribute to blood production at any given time. Nothing is known about the differences between individual stem cells that dictate their particular state of activation readiness. To examine such differences between individual stem cells, we determined the global gene expression profile of 12 single stem cells using microarrays. We showed that at least half of the genetic expression variability between 12 single cells profiled was due to biological variation in 44% of the genes analyzed. We also identified specific genes with high biological variance that are candidates for influencing the state of readiness of individual hematopoietic stem cells, and confirmed the variability of a subset of these genes using single-cell real-time PCR. Because apparent variation of some genes is likely due to technical factors, we estimated the degree of biological versus technical variation for each gene using identical RNA samples containing an RNA amount equivalent to that of single cells. This enabled us to identify a large cohort of genes with low technical variability whose expression can be reliably measured on the arrays at the single-cell level. These data have established that gene expression of individual stem cells varies widely, despite extremely high phenotypic homogeneity. Some of this variation is in key regulators of stem cell activity, which could account for the differential responses of particular stem cells to exogenous stimuli. The capacity to accurately interrogate individual cells for global gene expression will facilitate a systems approach to biological processes at a single-cell level

Method to estimate ISCO and ring-down frequencies in binary systems and consequences for gravitational wave data analysis

Recent advances in the description of compact binary systems have produced gravitational waveforms that include inspiral, merger and ring-down phases. Comparing results from numerical simulations with those of post-Newtonian (PN), and related, expansions has provided motivation for employing PN waveforms in near merger epochs when searching for gravitational waves and has encouraged the development of analytic fits to full numerical waveforms. The models and simulations do not yet cover the full binary coalescence parameter space. For these yet un-simulated regions, data analysts can still conduct separate inspiral, merger and ring-down searches. Improved knowledge about the end of the inspiral phase, the beginning of the merger, and the ring-down frequencies could increase the efficiency of both coherent inspiral-merger-ring-down (IMR) searches and searches over each phase separately. Insight can be gained for all three cases through a recently presented theoretical calculation, which, corroborated by the numerical results, provides an implicit formula for the final spin of the merged black holes, accurate to within 10% over a large parameter space. Knowledge of the final spin allows one to predict the end of the inspiral phase and the quasinormal mode ring-down frequencies, and in turn provides information about the bandwidth and duration of the merger. In this work we will discuss a few of the implications of this calculation for data analysis.Comment: Added references to section 3 14 pages 5 figures. Submitted to Classical and Quantum Gravit

Clinical Implementation of Chromosomal Microarray Analysis: Summary of 2513 Postnatal Cases

BACKGROUND: Array Comparative Genomic Hybridization (a-CGH) is a powerful molecular cytogenetic tool to detect genomic imbalances and study disease mechanism and pathogenesis. We report our experience with the clinical implementation of this high resolution human genome analysis, referred to as Chromosomal Microarray Analysis (CMA). METHODS AND FINDINGS: CMA was performed clinically on 2513 postnatal samples from patients referred with a variety of clinical phenotypes. The initial 775 samples were studied using CMA array version 4 and the remaining 1738 samples were analyzed with CMA version 5 containing expanded genomic coverage. Overall, CMA identified clinically relevant genomic imbalances in 8.5% of patients: 7.6% using V4 and 8.9% using V5. Among 117 cases referred for additional investigation of a known cytogenetically detectable rearrangement, CMA identified the majority (92.5%) of the genomic imbalances. Importantly, abnormal CMA findings were observed in 5.2% of patients (98/1872) with normal karyotypes/FISH results, and V5, with expanded genomic coverage, enabled a higher detection rate in this category than V4. For cases without cytogenetic results available, 8.0% (42/524) abnormal CMA results were detected; again, V5 demonstrated an increased ability to detect abnormality. Improved diagnostic potential of CMA is illustrated by 90 cases identified with 51 cryptic microdeletions and 39 predicted apparent reciprocal microduplications in 13 specific chromosomal regions associated with 11 known genomic disorders. In addition, CMA identified copy number variations (CNVs) of uncertain significance in 262 probands; however, parental studies usually facilitated clinical interpretation. Of these, 217 were interpreted as familial variants and 11 were determined to be de novo; the remaining 34 await parental studies to resolve the clinical significance. CONCLUSIONS: This large set of clinical results demonstrates the significantly improved sensitivity of CMA for the detection of clinically relevant genomic imbalances and highlights the need for comprehensive genetic counseling to facilitate accurate clinical correlation and interpretation

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

The Eleventh and Twelfth data releases of the Sloan Digital Sky Survey: Final data from SDSS-III

The third generation of the Sloan Digital Sky Survey (SDSS-III) tookdata from 2008 to 2014 using the original SDSS wide-field imager, theoriginal and an upgraded multi-object fiber-fed optical spectrograph, anew near-infrared high-resolution spectrograph, and a novel opticalinterferometer. All of the data from SDSS-III are now made public. Inparticular, this paper describes Data Release 11 (DR11) including alldata acquired through 2013 July, and Data Release 12 (DR12) adding dataacquired through 2014 July (including all data included in previous datareleases), marking the end of SDSS-III observing. Relative to ourprevious public release (DR10), DR12 adds one million new spectra ofgalaxies and quasars from the Baryon Oscillation Spectroscopic Survey(BOSS) over an additional 3000 deg2 of sky, more than triplesthe number of H-band spectra of stars as part of the Apache PointObservatory (APO) Galactic Evolution Experiment (APOGEE), and includesrepeated accurate radial velocity measurements of 5500 stars from theMulti-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS).The APOGEE outputs now include the measured abundances of 15 differentelements for each star. In total, SDSS-III added 5200 deg2 ofugriz imaging; 155,520 spectra of 138,099 stars as part of the SloanExploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey;2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and247,216 stars over 9376 deg2; 618,080 APOGEE spectra of156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since itsfirst light in 1998, SDSS has imaged over 1/3 of the Celestial sphere infive bands and obtained over five million astronomical spectra.Fil: Alam, Shadab. University of Carnegie Mellon; Estados UnidosFil: Albareti, Franco D.. Universidad Autónoma de Madrid; EspañaFil: Prieto, Carlos Allende. Universidad de La Laguna; EspañaFil: Anders, F.. Leibniz Institute For Astrophysics Potsdam; AlemaniaFil: Anderson, Scott F.. University of Utah; Estados UnidosFil: Anderton, Timothy. University of Utah; Estados UnidosFil: Andrews, Brett H.. Ohio State University; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Armengaud, Eric. Service de Physique Des Particules; FranciaFil: Aubourg, Éric. Université Paris Diderot - Paris 7; FranciaFil: Bailey, Stephen. Lawrence Berkeley National Laboratory; Estados UnidosFil: Basu, Sarbani. University of Yale; Estados UnidosFil: Bautista, Julian E.. Université Paris Diderot - Paris 7; FranciaFil: Beaton, Rachael L.. University of Virginia; Estados UnidosFil: Beers, Timothy C.. University of Notre Dame; Estados UnidosFil: Bender, Chad F.. Pennsylvania State University; Estados UnidosFil: Berlind, Andreas A.. Vanderbilt University; Estados UnidosFil: Beutler, Florian. Lawrence Berkeley National Laboratory; Estados UnidosFil: Bhardwaj, Vaishali. Lawrence Berkeley National Laboratory; Estados UnidosFil: Bird, Jonathan C.. Vanderbilt University; Estados UnidosFil: Bizyaev, Dmitry. Apache Point Observatory; Estados UnidosFil: Blake, Cullen H.. University of Pennsylvania; Estados UnidosFil: Blanton, Michael R.. New York University; Estados UnidosFil: Blomqvist, Michael. University of California at Irvine; Estados UnidosFil: Bochanski, John J.. University of Washington; Estados UnidosFil: Bolton, Adam S.. University of Utah; Estados UnidosFil: Bovy, Jo. Institute For Advanced Studies; Estados UnidosFil: Shelden, Bradley, A.. Apache Point Observatory; Estados UnidosFil: Brandt, W. N.. Pennsylvania State University; Estados UnidosFil: Brauer, D. E.. Leibniz Institute For Astrophysics Potsdam; AlemaniaFil: Nuza, Sebastian Ernesto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina. Institut Max Planck Fuer Gesellschaft. Max Planck Institute For Extraterrestrial Physics; AlemaniaFil: Scoccola, Claudia Graciela. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentin

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin