To have value, comparisons of high-throughput phenotyping methods need statistical tests of bias and variance

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson’s correlation coefficient (r) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method

Design of biomass value chains that are synergistic with the food-energy-water nexus: strategies and opportunities

Humanity’s future sustainable supply of energy, fuels and materials is aiming towards renewable sources such as biomass. Several studies on biomass value chains (BVCs) have demonstrated the feasibility of biomass in replacing fossil fuels. However, many of the activities along the chain can disrupt the food–energy–water (FEW) nexus given that these resource systems have been ever more interlinked due to increased global population and urbanisation. Essentially, the design of BVCs has to integrate the systems-thinking approach of the FEW nexus; such that, existing concerns on food, water and energy security, as well as the interactions of the BVCs with the nexus, can be incorporated in future policies. To date, there has been little to no literature that captures the synergistic opportunities between BVCs and the FEW nexus. This paper presents the first survey of process systems engineering approaches for the design of BVCs, focusing on whether and how these approaches considered synergies with the FEW nexus. Among the surveyed mathematical models, the approaches include multi-stage supply chain, temporal and spatial integration, multi-objective optimisation and uncertainty-based risk management. Although the majority of current studies are more focused on the economic impacts of BVCs, the mathematical tools can be remarkably useful in addressing critical sustainability issues in BVCs. Thus, future research directions must capture the details of food–energy–water interactions with the BVCs, together with the development of more insightful multi-scale, multi-stage, multi-objective and uncertainty-based approaches

Partnering With Patients and Families Living With Chronic Conditions to Coproduce Diagnostic Safety Through OurDX: A Previsit Online Engagement Tool

OBJECTIVE: Patients and families are key partners in diagnosis, but methods to routinely engage them in diagnostic safety are lacking. Policy mandating patient access to electronic health information presents new opportunities. We tested a new online tool ( OurDX ) that was codesigned with patients and families, to determine the types and frequencies of potential safety issues identified by patients/families with chronic health conditions and whether their contributions were integrated into the visit note. METHODS: Patients/families at 2 US healthcare sites were invited to contribute, through an online previsit survey: (1) visit priorities, (2) recent medical history/symptoms, and (3) potential diagnostic concerns. Two physicians reviewed patient-reported diagnostic concerns to verify and categorize diagnostic safety opportunities (DSOs). We conducted a chart review to determine whether patient contributions were integrated into the note. We used descriptive statistics to report implementation outcomes, verification of DSOs, and chart review findings. RESULTS: Participants completed OurDX reports in 7075 of 18 129 (39%) eligible pediatric subspecialty visits (site 1), and 460 of 706 (65%) eligible adult primary care visits (site 2). Among patients reporting diagnostic concerns, 63% were verified as probable DSOs. In total, probable DSOs were identified by 7.5% of pediatric and adult patients/families with underlying health conditions, respectively. The most common types of DSOs were patients/families not feeling heard; problems/delays with tests or referrals; and problems/delays with explanation or next steps. In chart review, most clinician notes included all or some patient/family priorities and patient-reported histories. CONCLUSIONS: OurDX can help engage patients and families living with chronic health conditions in diagnosis. Participating patients/families identified DSOs and most of their OurDX contributions were included in the visit note

Potential of global croplands and bioenergy crops for climate change mitigation through deployment for enhanced weathering.

Conventional row crop agriculture for both food and fuel is a source of carbon dioxide (CO2) and nitrous oxide (N2O) to the atmosphere, and intensifying production on agricultural land increases the potential for soil C loss and soil acidification due to fertilizer use. Enhanced weathering (EW) in agricultural soils-applying crushed silicate rock as a soil amendment-is a method for combating global climate change while increasing nutrient availability to plants. EW uses land that is already producing food and fuel to sequester carbon (C), and reduces N2O loss through pH buffering. As biofuel use increases, EW in bioenergy crops offers the opportunity to sequester CO2 while reducing fossil fuel combustion. Uncertainties remain in the long-term effects and global implications of large-scale efforts to directly manipulate Earth's atmospheric CO2 composition, but EW in agricultural lands is an opportunity to employ these soils to sequester atmospheric C while benefitting crop production and the global climate

Inducible Nucleosome Depletion at OREBP-Binding-Sites by Hypertonic Stress

Background: Osmotic Response Element-Binding Protein (OREBP), also known as TonEBP or NFAT5, is a unique transcription factor. It is hitherto the only known mammalian transcription factor that regulates hypertonic stress-induced gene transcription. In addition, unlike other monomeric members of the NFAT family, OREBP exists as a homodimer and it is the only transcription factor known to bind naked DNA targets by complete encirclement in vitro. Nevertheless, how OREBP interacts with target DNA, also known as ORE/TonE, and how it elicits gene transcription in vivo, remains unknown. Methodology: Using hypertonic induction of the aldose reductase (AR) gene activation as a model, we showed that OREs contained dynamic nucleosomes. Hypertonic stress induced a rapid and reversible loss of nucleosome(s) around the OREs. The loss of nucleosome(s) was found to be initiated by an OREBP-independent mechanism, but was significantly potentiated in the presence of OREBP. Furthermore, hypertonic induction of AR gene was associated with an OREBPdependent hyperacetylation of histones that spanned the 59 upstream sequences and at least some exons of the gene. Nevertheless, nucleosome loss was not regulated by the acetylation status of histone. Significance: Our findings offer novel insights into the mechanism of OREBP-dependent transcriptional regulation and provide a basis for understanding how histone eviction and transcription factor recruitment are coupled. © 2009 Tong et al.published_or_final_versio

An Improved Photometric Calibration of the Sloan Digital Sky Survey Imaging Data

We present an algorithm to photometrically calibrate wide field optical imaging surveys, that simultaneously solves for the calibration parameters and relative stellar fluxes using overlapping observations. The algorithm decouples the problem of "relative" calibrations, from that of "absolute" calibrations; the absolute calibration is reduced to determining a few numbers for the entire survey. We pay special attention to the spatial structure of the calibration errors, allowing one to isolate particular error modes in downstream analyses. Applying this to the Sloan Digital Sky Survey imaging data, we achieve ~1% relative calibration errors across 8500 sq.deg. in griz; the errors are ~2% for the u band. These errors are dominated by unmodelled atmospheric variations at Apache Point Observatory. These calibrations, dubbed "ubercalibration", are now public with SDSS Data Release 6, and will be a part of subsequent SDSS data releases.Comment: 16 pages, 17 figures, matches version accepted in ApJ. These calibrations are available at http://www.sdss.org/dr

The Sloan Digital Sky Survey Quasar Catalog IV. Fifth Data Release

We present the fourth edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog. The catalog contains 77,429 objects; this is an increase of over 30,000 entries since the previous edition. The catalog consists of the objects in the SDSS Fifth Data Release that have luminosities larger than M_i = -22.0 (in a cosmology with H_0 = 70 km/s/Mpc, Omega_M = 0.3, and Omega_Lambda = 0.7) have at least one emission line with FWHM larger than 1000 km/s, or have interesting/complex absorption features, are fainter than i=15.0, and have highly reliable redshifts. The area covered by the catalog is 5740 sq. deg. The quasar redshifts range from 0.08 to 5.41, with a median value of 1.48; the catalog includes 891 quasars at redshifts greater than four, of which 36 are at redshifts greater than five. Approximately half of the catalog quasars have i < 19; nearly all have i < 21. For each object the catalog presents positions accurate to better than 0.2 arcsec. rms per coordinate, five-band (ugriz) CCD-based photometry with typical accuracy of 0.03 mag, and information on the morphology and selection method. The catalog also contains basic radio, near-infrared, and X-ray emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra cover the wavelength region 3800--9200A at a spectral resolution of ~2000. The spectra can be retrieved from the public database using the information provided in the catalog. The average SDSS colors of quasars as a function of redshift, derived from the catalog entries, are presented in tabular form. Approximately 96% of the objects in the catalog were discovered by the SDSS.Comment: 37 pages, Accepted for publication in A

Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels

ACKNOWLEDGEMENTS We thank Dennis Ojima and Daniel L. Sanchez for their encouragement on this topic. The authors gratefully acknowledge partial support as follows: J.L.F., L.R.L., T.L.R., E.A.H.S., and J.J.S., the Sao Paulo Research Foundation (FAPESP grant# 2014/26767-9); J.L.F., L.R.L., K.P., and T.L.R., The Center for Bioenergy Innovation, a U.S. Department of Energy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science (grant# DE-AC05-00OR22725); L.R.L., the Sao Paulo Research Foundation, and the Link Foundation; J.L.F. and K.P., USDA/NIFA (grant# 2013-68005-21298 and 2017-67019-26327); T.L.R., USDA/NIFA (grant# 2012-68005-19703); D.S.L. and S.P.L., the Energy Biosciences Institute. Data availability The DayCent model (https://www2.nrel.colostate.edu/projects/daycent/) is freely available upon request. Specification of DayCent model runs and automated model initialization, calibration, scenario simulation, results analysis, and figure generation were implemented in Python 2.7, using the numpy module for data processing and the matplotlib module for figure generation. Analysis code is available in a version-controlled repository (https://github.com/johnlfield/Ecosystem_dynamics). A working copy of the code, all associated DayCent model inputs, and analysis outputs are also available in an online data repository (https://figshare.com/s/4c14ec168bd550db4bad; note this URL is for accessing a private version of the repository, and will eventually be replaced with an updated URL for the public version of the repository, which will only be accessible after the journal-specified embargo date).Peer reviewedPostprintPublisher PD