Functional genomics identifies a small secreted protein that plays a role during the biotrophic to necrotrophic shift in the root rot pathogen Phytophthora medicaginis

IntroductionHemibiotrophic Phytophthora are a group of agriculturally and ecologically important pathogenic oomycetes causing severe decline in plant growth and fitness. The lifestyle of these pathogens consists of an initial biotrophic phase followed by a switch to a necrotrophic phase in the latter stages of infection. Between these two phases is the biotrophic to necrotrophic switch (BNS) phase, the timing and controls of which are not well understood particularly in Phytophthora spp. where host resistance has a purely quantitative genetic basis.MethodsTo investigate this we sequenced and annotated the genome of Phytophthora medicaginis, causal agent of root rot and substantial yield losses to Fabaceae hosts. We analyzed the transcriptome of P. medicaginis across three phases of colonization of a susceptible chickpea host (Cicer arietinum) and performed co-regulatory analysis to identify putative small secreted protein (SSP) effectors that influence timing of the BNS in a quantitative pathosystem.ResultsThe genome of P. medicaginis is ~78 Mb, comparable to P. fragariae and P. rubi which also cause root rot. Despite this, it encodes the second smallest number of RxLR (arginine-any amino acid-leucine-arginine) containing proteins of currently sequenced Phytophthora species. Only quantitative resistance is known in chickpea to P. medicaginis, however, we found that many RxLR, Crinkler (CRN), and Nep1-like protein (NLP) proteins and carbohydrate active enzymes (CAZymes) were regulated during infection. Characterization of one of these, Phytmed_10271, which encodes an RxLR effector demonstrates that it plays a role in the timing of the BNS phase and root cell death.DiscussionThese findings provide an important framework and resource for understanding the role of pathogenicity factors in purely quantitative Phytophthora pathosystems and their implications to the timing of the BNS phase

Response surface methodology (RSM) to evaluate moisture effects on corn stover in recovering xylose by DEO hydrolysis

Response surface methodology (RSM), based on a 2(2) full factorial design, evaluated the moisture effects in recovering xylose by diethyloxalate (DEO) hydrolysis. Experiments were carried out in laboratory reactors (10 mL glass ampoules) containing corn stover (0.5 g) properly ground. The ampoules were kept at 160 degrees C for 90 min.(-) Both DEO concentration and corn stover moisture content were statistically significant at 99% confidence level. The maximum xylose recovery by the response surface methodology was achieved employing both DEO concentration and corn stover moisture at near their highest levels area. We amplified this area by using an overlay plot as a graphical optimization using a response of xylose recovery more than 80%. The mathematical statistical model was validated by testing a specific condition in the satisfied overlay plot area. Experimentally, a maximum xylose recovery (81.2%) was achieved by using initial corn stover moisture of 60% and a DEO concentration of 4% w/w. The mathematical statistical model showed that xylose recovery increases during DEO corn stover acid hydrolysis as the corn stover moisture level increases. This observation could be important during the harvesting of corn before it is fully dried in the field. The corn stover moisture was an important variable to improve xylose recovery by DEO acid hydrolysis. (c) 2011 Elsevier Ltd. All rights reserved.CNPq, Brazil [200702/2006-8

Effect of treatment of gestational diabetes mellitus on pregnancy outcomes

Copyright © 2005 Massachusetts Medical Society.Background: We conducted a randomized clinical trial to determine whether treatment of women with gestational diabetes mellitus reduced the risk of perinatal complications. Methods: We randomly assigned women between 24 and 34 weeks’ gestation who had gestational diabetes to receive dietary advice, blood glucose monitoring, and insulin therapy as needed (the intervention group) or routine care. Primary outcomes included serious perinatal complications (defined as death, shoulder dystocia, bone fracture, and nerve palsy), admission to the neonatal nursery, jaundice requiring phototherapy, induction of labor, cesarean birth, and maternal anxiety, depression, and health status. Results: The rate of serious perinatal complications was significantly lower among the infants of the 490 women in the intervention group than among the infants of the 510 women in the routine-care group (1 percent vs. 4 percent; relative risk adjusted for maternal age, race or ethnic group, and parity, 0.33; 95 percent confidence interval, 0.14 to 0.75; P=0.01). However, more infants of women in the intervention group were admitted to the neonatal nursery (71 percent vs. 61 percent; adjusted relative risk, 1.13; 95 percent confidence interval, 1.03 to 1.23; P=0.01). Women in the intervention group had a higher rate of induction of labor than the women in the routine-care group (39 percent vs. 29 percent; adjusted relative risk, 1.36; 95 percent confidence interval, 1.15 to 1.62; P<0.001), although the rates of cesarean delivery were similar (31 percent and 32 percent, respectively; adjusted relative risk, 0.97; 95 percent confidence interval, 0.81 to 1.16; P=0.73). At three months post partum, data on the women’s mood and quality of life, available for 573 women, revealed lower rates of depression and higher scores, consistent with improved health status, in the intervention group. Conclusions: Treatment of gestational diabetes reduces serious perinatal morbidity and may also improve the woman’s health-related quality of life.Caroline A. Crowther, Janet E. Hiller, John R. Moss, Andrew J. McPhee, William S. Jeffries and Jeffrey S. Robinso

The Gillings Sampler – An electrostatic air sampler as an alternative method for aerosol in vitro exposure studies

There is growing interest in studying the toxicity and health risk of exposure to multi-pollutant mixtures found in ambient air, and the U.S. Environmental Protection Agency (EPA) is moving towards setting standards for these types of mixtures. Additionally, the Health Effects Institute's strategic plan aims to develop and apply next-generation multi-pollutant approaches to understanding the health effects of air pollutants. There's increasing concern that conventional in vitro exposure methods are not adequate to meet EPA's strategic plan to demonstrate a direct link between air pollution and health effects. To meet the demand for new in vitro technology that better represents direct air-to-cell inhalation exposures, a new system that exposes cells at the air-liquid interface was developed. This new system, named the Gillings Sampler, is a modified two-stage electrostatic precipitator that provides a viable environment for cultured cells. Polystyrene latex spheres were used to determine deposition efficiencies (38-45%), while microscopy and imaging techniques were used to confirm uniform particle deposition. Negative control A549 cell exposures indicated the sampler can be operated for up to 4 hours without inducing any significant toxic effects on cells, as measured by lactate dehydrogenase (LDH) and interleukin-8 (IL-8). A novel positive aerosol control exposure method, consisting of a p-tolualdehyde (TOLALD) impregnated mineral oil aerosol (MOA), was developed to test this system. Exposures to the toxic MOA at a 1 ng/cm2 dose of TOLALD yielded a reproducible 1.4 and 2 fold increase in LDH and IL-8 mRNA levels over controls. This new system is intended to be used as an alternative research tool for aerosol in vitro exposure studies. While further testing and optimization is still required to produce a “commercially ready” system, it serves as a stepping-stone in the development of cost-effective in vitro technology that can be made accessible to researchers in the near future

A View of Tropical Cyclones from Above: The Tropical Cyclone Intensity Experiment

Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes

Discovering collectively informative descriptors from high-throughput experiments

<p>Abstract</p> <p>Background</p> <p>Improvements in high-throughput technology and its increasing use have led to the generation of many highly complex datasets that often address similar biological questions. Combining information from these studies can increase the reliability and generalizability of results and also yield new insights that guide future research.</p> <p>Results</p> <p>This paper describes a novel algorithm called BLANKET for symmetric analysis of two experiments that assess informativeness of descriptors. The experiments are required to be related only in that their descriptor sets intersect substantially and their definitions of case and control are consistent. From resulting lists of n descriptors ranked by informativeness, BLANKET determines <b>shortlists </b>of descriptors from each experiment, generally of different lengths p and q. For any pair of shortlists, four numbers are evident: the number of descriptors appearing in both shortlists, in exactly one shortlist, or in neither shortlist. From the associated contingency table, BLANKET computes Right Fisher Exact Test (RFET) values used as scores over a plane of possible pairs of shortlist lengths <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr></abbrgrp>. BLANKET then chooses a pair or pairs with RFET score less than a threshold; the threshold depends upon n and shortlist length limits and represents a quality of intersection achieved by less than 5% of random lists.</p> <p>Conclusions</p> <p>Researchers seek within a universe of descriptors some minimal subset that collectively and efficiently predicts experimental outcomes. Ideally, any smaller subset should be insufficient for reliable prediction and any larger subset should have little additional accuracy. As a method, BLANKET is easy to conceptualize and presents only moderate computational complexity. Many existing databases could be mined using BLANKET to suggest optimal sets of predictive descriptors.</p

Hybridization and adaptive evolution of diverse Saccharomyces species for cellulosic biofuel production

Additional file 15. Summary of whole genome sequencing statistics

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals