107 research outputs found
Ethofumesate-resistant annual bluegrass (Poa annua) in grass seed production systems
The prolific seed production and polyploidy of annual bluegrass allow for the rapid development of herbicide resistance. Ethofumesate-resistant annual bluegrass plants were identified in the 1990s in grass seed production in Oregon, but their prevalence and distribution are not well documented. Therefore a dose–response experiment was initiated to determine the potential level of ethofumesate resistance in seed production systems. Seeds from 55 annual bluegrass populations were obtained from three sources: seed production fields (31 populations), the seed cleaning process (6 populations), and seed testing lots prior to retail distribution (18 populations). Additionally, two populations, one with known ethofumesate resistance and one with known susceptibility, were identified in preliminary testing and used as controls in this experiment. Seed from each collected population was increased. Individual seedlings were then transplanted into separate cone-tainers, grown to a size of 2 to 3 tillers in the greenhouse, and then sprayed using a compressed air track spray chamber with 10 doses of ethofumesate at 0, 0.56, 1.1, 2.8, 5.6, 8.4, 11.2, 16.8, 22.4, and 44.8 kg ai ha−1, with 0.84 to 2.2 kg ha−1 as the label application rate for perennial ryegrass. The resistant to susceptible ratio of populations across all sources ranged from 0.5 to 5.5. The most resistant populations found in production fields, seed cleaning, and seed testing lots had the effective dose necessary to kill 50% of the population (ED50) of 12.1, 9.4, and 13.1 kg ha−1, respectively. Furthermore, 68% of the populations found in production fields had ED50 higher than 6 kg ha−1, indicating common annual bluegrass resistance in grass seed production. As such, growers should implement integrated weed management strategies, as herbicides alone will likely be ineffective at controlling annual bluegrass
A cellular trafficking signal in the SIV envelope protein cytoplasmic domain is strongly selected for in pathogenic infection
The HIV/SIV envelope glycoprotein (Env) cytoplasmic domain contains a highly conserved Tyr-based trafficking signal that mediates both clathrin-dependent endocytosis and polarized sorting. Despite extensive analysis, the role of these functions in viral infection and pathogenesis is unclear. An SIV molecular clone (SIVmac239) in which this signal is inactivated by deletion of Gly-720 and Tyr-721 (SIVmac239ΔGY), replicates acutely to high levels in pigtail macaques (PTM) but is rapidly controlled. However, we previously reported that rhesus macaques and PTM can progress to AIDS following SIVmac239ΔGY infection in association with novel amino acid changes in the Env cytoplasmic domain. These included an R722G flanking the ΔGY deletion and a nine nucleotide deletion encoding amino acids 734–736 (ΔQTH) that overlaps the rev and tat open reading frames. We show that molecular clones containing these mutations reconstitute signals for both endocytosis and polarized sorting. In one PTM, a novel genotype was selected that generated a new signal for polarized sorting but not endocytosis. This genotype, together with the ΔGY mutation, was conserved in association with high viral loads for several months when introduced into naïve PTMs. For the first time, our findings reveal strong selection pressure for Env endocytosis and particularly for polarized sorting during pathogenic SIV infection in vivo
Enabling microbial syringol conversion through structure-guided protein engineering
Microbial conversion of aromatic compounds is an emerging and promising strategy for valorization of the plant biopolymer lignin. A critical and often rate-limiting reaction in aromatic catabolism is O-aryl-demethylation of the abundant aromatic methoxy groups in lignin to form diols, which enables subsequent oxidative aromatic ring-opening. Recently, a cytochrome P450 system, GcoAB, was discovered to demethylate guaiacol (2-methoxyphenol), which can be produced from coniferyl alcohol-derived lignin, to form catechol. However, native GcoAB has minimal ability to demethylate syringol (2,6-dimethoxyphenol), the analogous compound that can be produced from sinapyl alcohol-derived lignin. Despite the abundance of sinapyl alcohol-based lignin in plants, no pathway for syringol catabolism has been reported to date. Here we used structure-guided protein engineering to enable microbial syringol utilization with GcoAB. Specifically, a phenylalanine residue (GcoA-F169) interferes with the binding of syringol in the active site, and on mutation to smaller amino acids, efficient syringol O-demethylation is achieved. Crystallography indicates that syringol adopts a productive binding pose in the variant, which molecular dynamics simulations trace to the elimination of steric clash between the highly flexible side chain of GcoA-F169 and the additional methoxy group of syringol. Finally, we demonstrate in vivo syringol turnover in Pseudomonas putida KT2440 with the GcoA-F169A variant. Taken together, our findings highlight the significant potential and plasticity of cytochrome P450 aromatic O-demethylases in the biological conversion of lignin-derived aromatic compounds
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Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US
This article contains supporting information online at http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2113561119/-/DCSupplemental.Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Integrative Biolog
Assessing the impact of COVID-19 on liver cancer management (CERO-19).
BACKGROUND & AIMS: The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems and it may have heavily impacted patients with liver cancer (LC). Herein, we evaluated whether the schedule of LC screening or procedures has been interrupted or delayed because of the COVID-19 pandemic. METHODS: An international survey evaluated the impact of the COVID-19 pandemic on clinical practice and clinical trials from March 2020 to June 2020, as the first phase of a multicentre, international, and observational project. The focus was on patients with hepatocellular carcinoma or intrahepatic cholangiocarcinoma, cared for around the world during the first COVID-19 pandemic wave. RESULTS: Ninety-one centres expressed interest to participate and 76 were included in the analysis, from Europe, South America, North America, Asia, and Africa (73.7%, 17.1%, 5.3%, 2.6%, and 1.3% per continent, respectively). Eighty-seven percent of the centres modified their clinical practice: 40.8% the diagnostic procedures, 80.9% the screening programme, 50% cancelled curative and/or palliative treatments for LC, and 41.7% modified the liver transplantation programme. Forty-five out of 69 (65.2%) centres in which clinical trials were running modified their treatments in that setting, but 58.1% were able to recruit new patients. The phone call service was modified in 51.4% of centres which had this service before the COVID-19 pandemic (n = 19/37). CONCLUSIONS: The first wave of the COVID-19 pandemic had a tremendous impact on the routine care of patients with liver cancer. Modifications in screening, diagnostic, and treatment algorithms may have significantly impaired the outcome of patients. Ongoing data collection and future analyses will report the benefits and disadvantages of the strategies implemented, aiding future decision-making. LAY SUMMARY: The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems globally. Herein, we assessed the impact of the first wave pandemic on patients with liver cancer and found that routine care for these patients has been majorly disrupted, which could have a significant impact on outcomes
2018 Research & Innovation Day Program
A one day showcase of applied research, social innovation, scholarship projects and activities.https://first.fanshawec.ca/cri_cripublications/1005/thumbnail.jp
CMB-S4: Forecasting Constraints on Primordial Gravitational Waves
CMB-S4---the next-generation ground-based cosmic microwave background (CMB)
experiment---is set to significantly advance the sensitivity of CMB
measurements and enhance our understanding of the origin and evolution of the
Universe, from the highest energies at the dawn of time through the growth of
structure to the present day. Among the science cases pursued with CMB-S4, the
quest for detecting primordial gravitational waves is a central driver of the
experimental design. This work details the development of a forecasting
framework that includes a power-spectrum-based semi-analytic projection tool,
targeted explicitly towards optimizing constraints on the tensor-to-scalar
ratio, , in the presence of Galactic foregrounds and gravitational lensing
of the CMB. This framework is unique in its direct use of information from the
achieved performance of current Stage 2--3 CMB experiments to robustly forecast
the science reach of upcoming CMB-polarization endeavors. The methodology
allows for rapid iteration over experimental configurations and offers a
flexible way to optimize the design of future experiments given a desired
scientific goal. To form a closed-loop process, we couple this semi-analytic
tool with map-based validation studies, which allow for the injection of
additional complexity and verification of our forecasts with several
independent analysis methods. We document multiple rounds of forecasts for
CMB-S4 using this process and the resulting establishment of the current
reference design of the primordial gravitational-wave component of the Stage-4
experiment, optimized to achieve our science goals of detecting primordial
gravitational waves for at greater than , or, in the
absence of a detection, of reaching an upper limit of at CL.Comment: 24 pages, 8 figures, 9 tables, submitted to ApJ. arXiv admin note:
text overlap with arXiv:1907.0447
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