Increased C3 productivity in Midwestern lawns since 1982 revealed by carbon isotopes in Amanita thiersii

How climate and rising carbon dioxide concentrations (pCO2) have influenced competition between C3 and C4 plants over the last 50 years is a critical uncertainty in climate change research. Here we used carbon isotope (δ13C) values of the saprotrophic lawn fungus Amanita thiersii to integrate the signal of C3 and C4 carbon in samples collected between 1982 and 2009 from the Midwestern USA. We then calculated 13C fractionation (Δ) to assess the balance between C3 and C4 photosynthesis as influenced by mean annual temperature (MAT), mean annual precipitation over a 30 year period (MAP‐30), and pCO2. Sporocarp Δ correlated negatively with MAT (−1.74‰ °C−1, 79% of variance) and positively with MAP (9.52‰ m−1, 15% of variance), reflecting the relative productivity of C3 and C4 grasses in lawns. In addition, Δ values correlated positively with pCO2 (0.072‰ ppm−1, 5% of variance). Reduced photorespiration with rising pCO2 accounted for 20% of this increased Δ, but the remaining 80% is consistent with increased assimilation of C3‐derived carbon by Amanita thiersii resulting from increased productivity of C3 grasses with rising pCO2. Between 1982 and 2009, pCO2 rose by 46 ppm and the relative contribution of C3 photosynthesis to Amanita thiersii carbon increased 18.5%. The δ13C value of Amanita thiersii may integrate both lawn maintenance practices and the physiological responses of turf grasses to rising CO2 concentrations

Study of localization in the quantum sawtooth map emulated on a quantum information processor

Quantum computers will be unique tools for understanding complex quantum systems. We report an experimental implementation of a sensitive, quantum coherence-dependent localization phenomenon on a quantum information processor (QIP). The localization effect was studied by emulating the dynamics of the quantum sawtooth map in the perturbative regime on a three-qubit QIP. Our results show that the width of the probability distribution in momentum space remained essentially unchanged with successive iterations of the sawtooth map, a result that is consistent with localization. The height of the peak relative to the baseline of the probability distribution did change, a result that is consistent with our QIP being an ensemble of quantum systems with a distribution of errors over the ensemble. We further show that the previously measured distributions of control errors correctly account for the observed changes in the probability distribution.Comment: 20 pages, 9 figure

Investigating investment in biopharmaceutical R&D

Recent studies have highlighted a reduction in projected financial returns associated with biopharmaceutical R&D, owing to decreased productivity, increases in costs and flattening revenue per new drug, prompting calls for dramatic revisions to R&D models. On the basis of previous financial modelling, the simplest hypothesis would be that new investment in such R&D should be minimal and focused on biologics in preference to small molecules, as the internal rate of return on investment for biologics projects has been reported to be higher (Nat. Rev. Drug Discov. 8, 609–610; 2009). We sought to discern how investors have been acting in recent years, and so examined investment trends in nascent public biopharmaceutical companies located in the United States by constructing a database of such companies that had US initial public offerings (IPOs) between 2010 and 2014 (see Supplementary information S1 (box) for details). We then analysed the characteristics of the 113 companies that met our inclusion criteria, including their corporate strategy and therapeutic modality focus. Here, we present the key findings from this analysis and discuss its implications based on our own financial modelling.United States. National Institutes of Health (NIANIH/R01AG043560

Clustered alignments of gene-expression time series data

Motivation: Characterizing and comparing temporal gene-expression responses is an important computational task for answering a variety of questions in biological studies. Algorithms for aligning time series represent a valuable approach for such analyses. However, previous approaches to aligning gene-expression time series have assumed that all genes should share the same alignment. Our work is motivated by the need for methods that identify sets of genes that differ in similar ways between two time series, even when their expression profiles are quite different

A Semi-Supervised Method for Predicting Transcription Factor–Gene Interactions in Escherichia coli

While Escherichia coli has one of the most comprehensive datasets of experimentally verified transcriptional regulatory interactions of any organism, it is still far from complete. This presents a problem when trying to combine gene expression and regulatory interactions to model transcriptional regulatory networks. Using the available regulatory interactions to predict new interactions may lead to better coverage and more accurate models. Here, we develop SEREND (SEmi-supervised REgulatory Network Discoverer), a semi-supervised learning method that uses a curated database of verified transcriptional factor–gene interactions, DNA sequence binding motifs, and a compendium of gene expression data in order to make thousands of new predictions about transcription factor–gene interactions, including whether the transcription factor activates or represses the gene. Using genome-wide binding datasets for several transcription factors, we demonstrate that our semi-supervised classification strategy improves the prediction of targets for a given transcription factor. To further demonstrate the utility of our inferred interactions, we generated a new microarray gene expression dataset for the aerobic to anaerobic shift response in E. coli. We used our inferred interactions with the verified interactions to reconstruct a dynamic regulatory network for this response. The network reconstructed when using our inferred interactions was better able to correctly identify known regulators and suggested additional activators and repressors as having important roles during the aerobic–anaerobic shift interface

pGQL: A probabilistic graphical query language for gene expression time courses

<p>Abstract</p> <p>Background</p> <p>Timeboxes are graphical user interface widgets that were proposed to specify queries on time course data. As queries can be very easily defined, an exploratory analysis of time course data is greatly facilitated. While timeboxes are effective, they have no provisions for dealing with noisy data or data with fluctuations along the time axis, which is very common in many applications. In particular, this is true for the analysis of gene expression time courses, which are mostly derived from noisy microarray measurements at few unevenly sampled time points. From a data mining point of view the robust handling of data through a sound statistical model is of great importance.</p> <p>Results</p> <p>We propose probabilistic timeboxes, which correspond to a specific class of Hidden Markov Models, that constitutes an established method in data mining. Since HMMs are a particular class of probabilistic graphical models we call our method Probabilistic Graphical Query Language. Its implementation was realized in the free software package pGQL. We evaluate its effectiveness in exploratory analysis on a yeast sporulation data set.</p> <p>Conclusions</p> <p>We introduce a new approach to define dynamic, statistical queries on time course data. It supports an interactive exploration of reasonably large amounts of data and enables users without expert knowledge to specify fairly complex statistical models with ease. The expressivity of our approach is by its statistical nature greater and more robust with respect to amplitude and frequency fluctuation than the prior, deterministic timeboxes.</p

Chemoradiotherapy in octogenarians as primary treatment for muscle-invasive bladder cancer

Introduction: While radical cystectomy is the gold standard for muscle-invasive bladder cancer (MIBC), in octogenarians cystectomy results in a higher perioperative mortality rate (6.8‒11.1%) than in younger patients (2.2%). Trimodality therapy is a bladder-sparing regimen composed of transurethral resection of bladder tumour (TURBT) and chemoradiotherapy, with intent for salvage cystectomy, and has a 62.5‒90% initial complete response rate. In this study, we evaluate TURBT and chemoradiotherapy without salvage cystectomy in medically inoperable octogenarian patients. Methods: We identified a retrospective cohort of patients aged 80‒89 years with invasive urothelial carcinoma who received combination chemoradiotherapy between 2008 and June 2014. Outcomes were evaluated by Kaplan-Meier (KM) and Cox regression. Results: In 40 patients, the mean age was 84.5 years (interquartile range [IQR] 83‒86). Seventeen patients received hypofractionated, low-dose radiotherapy (LD) (37.5‒40 Gy), while 23 received conventionally fractionated radiotherapy (high-dose [HD]) (50‒65 Gy). Mean overall survival (OS) was 20.7 months (IQR 12.75‒23.25), while mean recurrence-free survival (RFS) was 13.75 months (IQR 3.75‒16.5). Patients receiving HD radiotherapy showed improved OS and local RFS (LRFS) without significant differences in Grade 3‒4 toxicities. Univariate Cox regression identified hydronephrosis as a predictor of worse OS and local recurrence and HD radiotherapy as a predictor of improved OS and local recurrence rates. Multivariate Cox regression identified hydronephrosis to be a significant predictor of LRFS. Conclusions: Primary chemoradiotherapy for inoperable patients with MIBC resulted in a three-year OS of 54.9% (comparable to cystectomy) and three-year RFS of 42.3%. Superior outcomes were associated with more aggressive chemoradiotherapy treatment. The results of the local control subanalyses in this study are hypothesis-generating due to the limited patient numbers in the cohort

Comparison of Turbulence-Induced Scintillations for Multi-Wavelength Laser Beacons Over Tactical (7 km) and Long (149 km) Atmospheric Propagation Paths

We report results of the experimental analysis of atmospheric effects on laser beam propagation over two distinctive propagation paths: a long-range (149 km) propagation path between Mauna Loa (Island of Hawaii) and Haleakala (Island of Maui) mountains, and a tactical-range (7 km) propagation path between the roof of the Dayton Veterans Administration Medical Center (VAMC) and the Intelligent Optics Laboratory (IOL/UD) located on the 5th floor of the University of Dayton College Park Center building. Both testbeds include three laser beacons operating at wavelengths 532 nm, 1064 nm, and 1550 nm and a set of identical optical receiver systems with fast-framing IR cameras for simultaneous measurements of pupil and focal plane intensity distributions. The results reported here are focused on analysis of intensity scintillations that were simultaneously measured at three wavelengths. Comparison of experimental results shows significant differences in the physics of atmospheric turbulence impact on laser beam propagation over the long- and tactical-range distances