Biomass Crop Production: Benefits for Soil Quality and Carbon Sequestration

Research at three locations in the southeastern US is quantifying changes in soil quality and soil carbon storage that occur during production of biomass crops compared with row crops. After three growing seasons, soil quality improved and soil carbon storage increased on plots planted to cottonwood, sycamore, sweetgum with a cover crop, switchgrass, and no-till corn. For tree crops, sequestered belowground carbon was found mainly in stumps and large roots. At the TN site, the coarse woody organic matter storage belowground was 1.3 Mg ha{sup {minus}1}yr{sup {minus}1}, of which 79% was stumps and large roots and 21% fine roots. Switchgrass at the AL site also stored considerable carbon belowground as coarse roots. Most of the carbon storage occurred mainly in the upper 30 cw although coarse roots were found to depths of greater than 60 cm. Biomass crops contributed to improvements in soil physical quality as well as increasing belowground carbon sequestration. The distribution and extent of carbon sequestration depends on the growth characteristics and age of the individual biomass crop species. Time and increasing crop maturity will determine the potential of these biomass crops to significantly contribute to the overall national goal of increasing carbon sequestration and reducing greenhouse gas emissions

Novel mesothelin antibodies enable crystallography of the intact mesothelin ectodomain and engineering of potent, T cell-engaging bispecific therapeutics

Mesothelin is a glypiated, cell-surface glycoprotein expressed at low levels on normal mesothelium but overexpressed by many cancers. Implicated in cell adhesion and multiple signaling pathways, mesothelin’s precise biological function and overall structure remain undefined. Antibodies targeting mesothelin have been engineered into immunotoxins, antibody-drug conjugates, CAR-T cells, or bispecific T cell engagers as candidate therapeutics but most face challenges, including binding epitopes that are not optimal for selected modalities. Here we describe the isolation and characterization of a novel anti-mesothelin antibody, 1A12, including crystallographic mapping of the 1A12 epitope in relation to other antibodies (amatuximab, anetumab). 1A12 possesses uniquely favorable properties, including a membrane-proximal epitope, and enabled structure determination of the complete mesothelin ectodomain. We incorporated 1A12 into two different bispecific T cell engaging architectures with various anti-CD3 co-targeting elements as candidate therapeutics, demonstrating in vitro functionality and potency

Incentives for retaining and motivating health workers in Pacific and Asian countries

This paper was initiated by the Australian Agency for International Development (AusAID) after identifying the need for an in-depth synthesis and analysis of available literature and information on incentives for retaining health workers in the Asia-Pacific region. The objectives of this paper are to

Pandemic Influenza Due to pH1N1/2009 Virus: Estimation of Infection Burden in Reunion Island through a Prospective Serosurvey, Austral Winter 2009

International audienceBACKGROUND: To date, there is little information that reflects the true extent of spread of the pH1N1/2009v influenza pandemic at the community level as infection often results in mild or no clinical symptoms. This study aimed at assessing through a prospective study, the attack rate of pH1N1/2009 virus in Reunion Island and risk factors of infection, during the 2009 season.METHODOLOGY/PRINCIPAL FINDINGS: A serosurvey was conducted during the 2009 austral winter, in the frame of a prospective population study. Pairs of sera were collected from 1687 individuals belonging to 772 households, during and after passage of the pandemic wave. Antibodies to pH1N1/2009v were titered using the hemagglutination inhibition assay (HIA) with titers ≥ 1/40 being considered positive. Seroprevalence during the first two weeks of detection of pH1N1/2009v in Reunion Island was 29.8% in people under 20 years of age, 35.6% in adults (20-59 years) and 73.3% in the elderly (≥ 60 years) (P<0.0001). Baseline corrected cumulative incidence rates, were 42.9%, 13.9% and 0% in these age groups respectively (P<0.0001). A significant decline in antibody titers occurred soon after the passage of the epidemic wave. Seroconversion rates to pH1N1/2009 correlated negatively with age: 63.2%, 39.4% and 16.7%, in each age group respectively (P<0.0001). Seroconversion occurred in 65.2% of individuals who were seronegative at inclusion compared to 6.8% in those who were initially seropositive.CONCLUSIONS: Seroincidence of pH1N1/2009v infection was three times that estimated from clinical surveillance, indicating that almost two thirds of infections occurring at the community level have escaped medical detection. People under 20 years of age were the most affected group. Pre-epidemic titers ≥ 1/40 prevented seroconversion and are likely protective against infection. A concern was raised about the long term stability of the antibody responses

The Role of Host Genetics in Susceptibility to Influenza: A Systematic Review

Background: The World Health Organization has identified studies of the role of host genetics on susceptibility to severe influenza as a priority. A systematic review was conducted to summarize the current state of evidence on the role of host genetics in susceptibility to influenza (PROSPERO registration number: CRD42011001380). Methods and Findings: PubMed, Web of Science, the Cochrane Library, and OpenSIGLE were searched using a pre-defined strategy for all entries up to the date of the search. Two reviewers independently screened the title and abstract of 1,371 unique articles, and 72 full text publications were selected for inclusion. Mouse models clearly demonstrate that host genetics plays a critical role in susceptibility to a range of human and avian influenza viruses. The Mx genes encoding interferon inducible proteins are the best studied but their relevance to susceptibility in humans is unknown. Although the MxA gene should be considered a candidate gene for further study in humans, over 100 other candidate genes have been proposed. There are however no data associating any of these candidate genes to susceptibility in humans, with the only published study in humans being under-powered. One genealogy study presents moderate evidence of a heritable component to the risk of influenza-associated death, and while the marked familial aggregation of H5N1 cases is suggestive of host genetic factors, this remains unproven. Conclusion: The fundamental question ‘‘Is susceptibility to severe influenza in humans heritable?’ ’ remains unanswered. No

Real-time numerical forecast of global epidemic spreading: Case study of 2009 A/H1N1pdm

Background Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches. Methods We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability. Results Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model. Conclusions Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models