A robust method for the amplification of RNA in the sense orientation

BACKGROUND: Small quantities of RNA (1–4 μg total RNA) available from biological samples frequently require a single round of amplification prior to analysis, but current amplification strategies have limitations that may restrict their usefulness in downstream genomic applications. The Eberwine amplification method has been extensively validated but is limited by its ability to produce only antisense RNA. Alternatives lack extensive validation and are often confounded by problems with bias or yield attributable to their greater biological and technical complexity. RESULTS: To overcome these limitations, we have developed a straightforward and robust protocol for amplification of RNA in the sense orientation. This protocol is based upon Eberwine's method but incorporates elements of more recent amplification techniques while avoiding their complexities. Our technique yields greater than 100-fold amplification, generates long transcript, and produces mRNA that is well suited for use with microarray applications. Microarrays performed with RNA amplified using this protocol demonstrate minimal amplification bias and high reproducibility. CONCLUSION: The protocol we describe here is readily adaptable for the production of sense or antisense, labeled or unlabeled RNA from intact or partially-degraded prokaryotic or eukaryotic total RNA. The method outperforms several commercial RNA amplification kits and can be used in conjunction with a variety of microarray platforms, such as cDNA arrays, oligonucleotide arrays, and Affymetrix GeneChip™ arrays

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM

The Magnetic Field in Taurus Probed by Infrared Polarization

We present maps of the plane-of-sky magnetic field within two regions of the Taurus molecular cloud: one in the dense core L1495/B213 filament, the other in a diffuse region to the west. The field is measured from the polarization of background starlight seen through the cloud. In total, we measured 287 high-quality near-infrared polarization vectors in these regions. In L1495/B213, the percent polarization increases with column density up to Av ~ 9 mag, the limits of our data. The Radiative Torques model for grain alignment can explain this behavior, but models that invoke turbulence are inconsistent with the data. We also combine our data with published optical and near-infrared polarization measurements in Taurus. Using this large sample, we estimate the strength of the plane-of-sky component of the magnetic field in nine subregions. This estimation is done with two different techniques that use the observed dispersion in polarization angles. Our values range from 5-82 microgauss and tend to be higher in denser regions. In all subregions, the critical index of the mass-to-magnetic flux ratio is sub-unity, implying that Taurus is magnetically supported on large scales (~2 pc). Within the region observed, the B213 filament makes a sharp turn to the north and the direction of the magnetic field also takes a sharp turn, switching from being perpendicular to the filament to becoming parallel. This behavior can be understood if we are observing the rim of a bubble. We argue that it has resulted from a supernova remnant associated with a recently discovered nearby gamma-ray pulsar.Comment: Accepted into the Astrophysical Journal. 20 pages in emulateapj format including 10 figures and 4 table

Fast as Potoroo: Radio Continuum Detection of a Bow-Shock Pulsar Wind Nebula Powered by Pulsar J1638-4713

We report the discovery of a bow-shock pulsar wind nebula (PWN), named Potoroo, and the detection of a young pulsar J1638-4713 that powers the nebula. We present a radio continuum study of the PWN based on 20-cm observations obtained from the Australian Square Kilometre Array Pathfinder (ASKAP) and MeerKAT. PSR J1638-4713 was identified using Parkes radio telescope observations at frequencies above 3 GHz. The pulsar has the second-highest dispersion measure of all known radio pulsars (1553 pc/cm^3), a spin period of 65.74 ms and a spin-down luminosity of 6.1x10^36 erg/s. The PWN has a cometary morphology and one of the greatest projected lengths among all the observed pulsar radio tails, measuring over 21 pc for an assumed distance of 10 kpc. The remarkably long tail and atypically steep radio spectral index are attributed to the interplay of a supernova reverse shock and the PWN. The originating supernova remnant is not known so far. We estimated the pulsar kick velocity to be in the range of 1000-2000 km/s for ages between 23 and 10 kyr. The X-ray counterpart found in Chandra data, CXOU J163802.6-471358, shows the same tail morphology as the radio source but is shorter by a factor of 10. The peak of the X-ray emission is offset from the peak of the radio total intensity (Stokes I) emission by approximately 4.7", but coincides well with circularly polarised (Stokes V) emission. No infrared counterpart was found.Comment: 16 pages, 8 figures, 4 tables; Accepted for publication in PASA on 18 Jan 202

Why Is There a Lack of Consensus on Molecular Subgroups of Glioblastoma? Understanding the Nature of Biological and Statistical Variability in Glioblastoma Expression Data

Gene expression patterns characterizing clinically-relevant molecular subgroups of glioblastoma are difficult to reproduce. We suspect a combination of biological and analytic factors confounds interpretation of glioblastoma expression data. We seek to clarify the nature and relative contributions of these factors, to focus additional investigations, and to improve the accuracy and consistency of translational glioblastoma analyses.We analyzed gene expression and clinical data for 340 glioblastomas in The Cancer Genome Atlas (TCGA). We developed a logic model to analyze potential sources of biological, technical, and analytic variability and used standard linear classifiers and linear dimensional reduction algorithms to investigate the nature and relative contributions of each factor.Commonly-described sources of classification error, including individual sample characteristics, batch effects, and analytic and technical noise make measurable but proportionally minor contributions to inconsistent molecular classification. Our analysis suggests that three, previously underappreciated factors may account for a larger fraction of classification errors: inherent non-linear/non-orthogonal relationships among the genes used in conjunction with classification algorithms that assume linearity; skewed data distributions assumed to be Gaussian; and biologic variability (noise) among tumors, of which we propose three types.Our analysis of the TCGA data demonstrates a contributory role for technical factors in molecular classification inconsistencies in glioblastoma but also suggests that biological variability, abnormal data distribution, and non-linear relationships among genes may be responsible for a proportionally larger component of classification error. These findings may have important implications for both glioblastoma research and for translational application of other large-volume biological databases

Formation of the Isthmus of Panama

The formation of the Isthmus of Panama stands as one of the greatest natural events of the Cenozoic, driving profound biotic transformations on land and in the oceans. Some recent studies suggest that the Isthmus formed manymillions of years earlier than the widely recognized age of approximately 3 million years ago (Ma), a result that if true would revolutionize our understanding of environmental, ecological, and evolutionary change across the Americas. To bring clarity to the question of when the Isthmus of Panama formed, we provide an exhaustive review and reanalysis of geological, paleontological, and molecular records. These independent lines of evidence converge upon a cohesive narrative of gradually emerging land and constricting seaways,withformationof theIsthmus of Panama sensustricto around 2.8 Ma. The evidence used to support an older isthmus is inconclusive, and we caution against the uncritical acceptance of an isthmus before the Pliocene.Facultad de Ciencias Naturales y Muse

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -- corrected for geometrical effects -- is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO