Influence of soil texture and crop management on the productivity of miscanthus (Miscanthus × giganteus Greef et Deu.) in the Mediterranean

Biomass productivity is the main favorable trait of candidate bioenergy crops. Miscanthus × giganteus is a promising species, due to its high‐yield potential and positive traits including low nutrient requirements and potential for C sequestration in soils. However, miscanthus productivity appears to be mostly related to water availability in the soil. This is important, particularly in Mediterranean regions where the risk of summer droughts is high. To date, there have been no studies on miscanthus responses under different soil conditions, while only a few have investigated the role of different crop managements, such as irrigation and nitrogen fertilization, in the Mediterranean. Therefore, the effects of contrasting soil textures (i.e. silty‐clay‐loam vs. sandy‐loam) and alternative agricultural intensification regimes (i.e. rainfed vs. irrigated and 0, 50, 100 kg ha^?1 nitrogen fertilization), on miscanthus productivity were evaluated at three different harvest times for two consecutive years. Our results confirmed the importance of water availability in determining satisfactory yields in Mediterranean environments, and how soil and site characteristics strongly affect biomass production. We found that the aboveground dry yields varied between 5 Mg ha^?1 up to 29 Mg ha^?1. Conversely, nitrogen fertilization played only a minor role on crop productivity, and high fertilization levels were relatively inefficient. Finally, a marked decrease, of up to ?40%, in the aboveground yield occurred when the harvest time was delayed from autumn to winter. Overall, our results highlighted the importance of determining crop responses on a site‐by‐site basis, and that decisions on the optimal harvest time should be driven by the biomass end use and other long‐term considerations, such as yield stability and the maintenance of soil fertility.     

The economics of producing sustainable aviation fuel: a regional case study in Queensland,Australia

The airline industry has a strong interest in developing sustainable aviation fuels, in order to reduce their exposure to increasing oil prices and cost liability for greenhouse gas emissions. The feasibility and cost of producing sustainable biomass‐based jet fuels at a sufficient scale to materially address these issues is an enormous challenge. This paper builds directly on the biophysical study by H.T. Murphy, D.A. O'Connell, R.J. Raison, A.C. Warden, T.H. Booth, A. Herr, A.L. Braid, D.F. Crawford, J.A. Hayward, T. Javonovic, J.G. McIvor, M.H. O'Connor, M.L. Poole, D. Prestwidge, N. Raisbeck‐Brown & L. Rye, In review, which examined a 25 year scale‐up strategy to produce 5% of projected jet fuel demand in Australia in 2020 (470 mL) in the Fitzroy region of Queensland, Australia. The strategy was based on the use of a mixed ligno‐cellulosic biomass feedstock and assumed, for the sake of exploring and quantifying the scenario, a simplified two‐step conversion process – conversion of biomass to crude bio‐oil within the region, and upgrade to jet fuel at a central Brisbane facility. This paper provides details on the costs of production in this scenario, focusing on two different strategies for biomass utilization, and two types of novel small–medium scale conversion technologies. The cost analyses have taken into account technology learning curves, different economies of scale and key cost sensitivities. The cost of biomass‐based jet fuels is estimated to be between 0.70 and 1.90 The airline industry has a strong interest in developing sustainable aviation fuels, in order to reduce their exposure to increasing oil prices and cost liability for greenhouse gas emissions. The feasibility and cost of producing sustainable biomass‐based jet fuels at a sufficient scale to materially address these issues is an enormous challenge. This paper builds directly on the biophysical study by H.T. Murphy, D.A. O'Connell, R.J. Raison, A.C. Warden, T.H. Booth, A. Herr, A.L. Braid, D.F. Crawford, J.A. Hayward, T. Javonovic, J.G. McIvor, M.H. O'Connor, M.L. Poole, D. Prestwidge, N. Raisbeck‐Brown & L. Rye, In review, which examined a 25 year scale‐up strategy to produce 5% of projected jet fuel demand in Australia in 2020 (470 mL) in the Fitzroy region of Queensland, Australia. The strategy was based on the use of a mixed ligno‐cellulosic biomass feedstock and assumed, for the sake of exploring and quantifying the scenario, a simplified two‐step conversion process – conversion of biomass to crude bio‐oil within the region, and upgrade to jet fuel at a central Brisbane facility. This paper provides details on the costs of production in this scenario, focusing on two different strategies for biomass utilization, and two types of novel small–medium scale conversion technologies. The cost analyses have taken into account technology learning curves, different economies of scale and key cost sensitivities. The cost of biomass‐based jet fuels is estimated to be between 0.70 and 1.90 $ L^?1 when the efficiency of conversion of biomass to biocrude and subsequently to aviation fuel is varied by ±10% of published values, with an average value of 1.10 $ L^?1. This is within the range of the projected 2035 conventional jet fuel price of 1.50 $ L^?1. Therefore, biomass‐based jet fuel has the potential to contribute to supply of Australia's jet fuel needs in the future.     

Investigation of Repeat Client Drop-Out and Re-Enrolment Cycles in Fourteen Methadone Maintenance Treatment Clinics in Guangdong,China

ObjectiveClient adherence is vital for effective methadone maintenance treatment (MMT). This study explores the pattern and associated factors of client adherence, drop-out and re-enrolment in the Chinese MMT programme over the period of 2006–2013.MethodsThis retrospective study was conducted in 14 MMT clinics in Guangdong Province, China. We employed Kaplan-Meier survival analysis to estimate the rates of drop-out and re-enrolment of MMT clients and multivariate Cox regression to identify associated factors.ResultsAmong 1,512 study participants, 79% have experienced ‘drop-out’ during the 7-year study period. However, 82% ‘dropped-out’ clients resumed treatment at a later time. Low education level (junior high or below versus otherwise, HR = 1.21, 1.05–1.40), low methadone dosage in the first treatment episode (<50 ml versus ≥50 ml, HR = 1.84, 1.64–2.06) and higher proportion of positive urine test (≥50% versus<50%, HR = 3.72, 3.30–4.20) during the first treatment episode were strong predictors of subsequent drop-outs of the participants. Among the ‘dropped-out’ clients, being female (HR = 1.40, 1.23–1.60), being married (HR = 1.19, 1.09–1.30), and having a higher proportion of positive urine tests in the first treatment episode (≥50% versus<50%, HR = 1.35, 1.20–1.51) had greater likelihood of subsequent re-enrolment in MMT. Clients receiving lower methadone dosage (first treatment episode <50 ml versus ≥50 ml, HR = 1.12, 1.03–1.23; the last intake before drop-out <50 ml versus ≥50 ml, HR = 1.16, 1.04–1.30) were also more likely to re-enrol.ConclusionPersistent cycling in-and-out of clients in MMT programmes is common. Insufficient dosage and higher proportion of positive urine samples in the first treatment episode are the key determinants for subsequent client drop-out and re-enrolment. Interventions should target clients in their early stage of treatment to improve retention in the long term.     

High Sodium and Low Potassium Intake among Italian Children: Relationship with Age,Body Mass and Blood Pressure

Background

Hypertension is the leading cause of death in developed countries and reduction of salt intake is recommended as a key preventive measure.

Objective

To assess the dietary sodium and potassium intakes in a national sample of Italian children and adolescents and to examine their relationships with BMI and blood pressure (BP) in the framework of the MINISAL survey, a program supported by the Italian Ministry of Health.

Population and Methods

The study population included 1424 healthy subjects (766 boys, 658 girls) aged 6-18 years (mean age: 10.1±2.9) who were consecutively recruited in participating National Health Service centers in 10 Italian regions. Electrolyte intake was estimated from 24 hour urine collections tested for completeness by the concomitant measurement of creatinine content. Anthropometric indices and BP were measured with standardized procedures.

Results

The average estimated sodium intake was 129 mmol (7.4 g of salt) per day among boys and 117 mmol (6.7 g of salt) among girls. Ninety-three percent of the boys and 89% of the girls had a consumption higher than the recommended age-specific standard dietary target. The estimated average daily potassium intakes were 39 mmol (1.53 g) and 36 mmol (1.40 g), respectively, over 96% of the boys and 98% of the girls having a potassium intake lower than the recommended adequate intake. The mean sodium/potassium ratio was similar among boys and girls (3.5 and 3.4, respectively) and over 3-fold greater than the desirable level. Sodium intake was directly related to age, body mass and BP in the whole population.

Conclusions

The Italian pediatric population is characterized by excessive sodium and deficient potassium intake. These data suggest that future campaigns should focus on children and adolescents as a major target in the framework of a population strategy of cardiovascular prevention.     

Impact of the Uremic Milieu on the Osteogenic Potential of Mesenchymal Stem Cells

Human mesenchymal stem cells (hMSCs), the precursors of osteoblasts during osteogenesis, play a role in the balance of bone formation and resorption, but their functioning in uremia has not been well defined. To study the effects of the uremic milieu on osteogenic properties, we applied an in vitro assay culturing hMSCs in osteogenic medium supplemented with serum from healthy donors and from uremic patients on hemodialysis. Compared to control, serum from uremic patients induces, in hMSC cultures, a modification of several key regulators of bone remodeling, in particular a reduction of the ratio Receptor Activator of Nuclear factor Kappa B Receptor (RANKL) over osteoprotegerin, indicating an adaptive response of the system to favor osteogenesis over osteoclastosis. However, the levels of osteopontin, osteocalcin, and collagen type I, are increased in cell medium, while BMP-2, and alizarin red staining were decreased, pointing to a reduction of bone formation favoring resorption. Selected uremic toxins, such as p-cresylsulfate, p-cresylglucuronide, parathyroid hormone, indoxyl sulfate, asymmetric dimethylarginine, homocysteine, were able to mimic some of the effects of whole serum from uremic patients. Serum from cinacalcet-treated patients antagonizes these effects. Hydrogen sulfide (H2S) donors as well as hemodialysis treatment are able to induce beneficial effects. In conclusion, bone modifications in uremia are influenced by the capability of the uremic milieu to alter hMSC osteogenic differentiation. Cinacalcet, H2S donors and a hemodialysis session can ameliorate the hampered calcium deposition.     

Environmental Quality Assessment of Bizerte Lagoon (Tunisia) Using Living Foraminifera Assemblages and a Multiproxy Approach

This study investigated the environmental quality of the Bizerte Lagoon (Tunisia) through an integrated approach that combined environmental, biogeochemical, and living benthic foraminiferal analyses. Specifically, we analyzed the physicochemical parameters of the water and sediment. The textural, mineralogical, and geochemical characteristics of the sediment, including total organic carbon, total nitrogen, simultaneously extracted metals (SEM), acid volatile sulfides (AVS), chlorophyll a, CaCO₃, and changes in bacterial populations and carbon isotopes were measured. The SEM/AVS values indicated the presence of relatively high concentrations of toxic metals in only some areas. Foraminiferal assemblages were dominated by species such as A. parkinsoniana (20–91%), Bolivina striatula (<40%), Hopkinsina atlantica (<17%), and Bolivina ordinaria (<15%) that cannot be considered typical of impacted coastal lagoons both in Mediterranean and northeast Atlantic regions. The results of this work suggest that Bizerte Lagoon is a unique setting. This lagoon is populated by typical marine species that invaded this ecosystem, attracted not only by the prevailing favorable environmental conditions but also by the abundance and quality of food. The results indicate that the metal pollution found in some areas have a negative impact on the assemblages of foraminifera. At present, however, this negative impact is not highly alarming.     

Protectome Analysis: A New Selective Bioinformatics Tool for Bacterial Vaccine Candidate Discovery

New generation vaccines are in demand to include only the key antigens sufficient to confer protective immunity among the plethora of pathogen molecules. In the last decade, large-scale genomics-based technologies have emerged. Among them, the Reverse Vaccinology approach was successfully applied to the development of an innovative vaccine against Neisseria meningitidis serogroup B, now available on the market with the commercial name BEXSERO® (Novartis Vaccines). The limiting step of such approaches is the number of antigens to be tested in in vivo models. Several laboratories have been trying to refine the original approach in order to get to the identification of the relevant antigens straight from the genome. Here we report a new bioinformatics tool that moves a first step in this direction. The tool has been developed by identifying structural/functional features recurring in known bacterial protective antigens, the so called “Protectome space,” and using such “protective signatures” for protective antigen discovery. In particular, we applied this new approach to Staphylococcus aureus and Group B Streptococcus and we show that not only already known protective antigens were re-discovered, but also two new protective antigens were identified.Although vaccines based on attenuated pathogens as pioneered by Luis Pasteur have been shown to be extremely effective, safety and technical reasons recommend that new generation vaccines include few selected pathogen components which, in combination with immunostimulatory molecules, can induce long lasting protective responses. Such approach implies that the key antigens sufficient to confer protective immunity are singled out among the plethora of pathogen molecules. As it turns out, the search for such protective antigens can be extremely complicated.Genomic technologies have opened the way to new strategies in vaccine antigen discovery (1, 2, 3). Among them, Reverse Vaccinology (RV)¹ has proved to be highly effective, as demonstrated by the fact that a new Serogroup B Neisseria meningitidis (MenB) vaccine, incorporating antigens selected by RV, is now available to defeat meningococcal meningitis (4, 5). In essence, RV is based on the simple assumption that cloning all annotated proteins/genes and screening them against a robust and reliable surrogate-of-protection assay must lead to the identification of all protective antigens. Because most of the assays available for protective antigen selection involve animal immunization and challenge, the number of antigens to be tested represents a severe bottleneck of the entire process. For this reason, despite the fact that RV is a brute force, inclusive approach (“test-all-to-lose-nothing” type of approach) in their pioneered work of MenB vaccine discovery, Pizza and co-workers did not test the entire collection of MenB proteins but rather restricted their analysis to the ones predicted to be surface-localized. This was based on the evidence that for an anti-MenB vaccine to be protective bactericidal antibodies must be induced, a property that only surface-exposed antigens have. For the selection of surface antigens Pizza and co-workers mainly used PSORT and other available tools like MOTIFS and FINDPATTERNS to find proteins carrying localization-associated features such as transmembrane domains, leader peptides, and lipobox and outer membrane anchoring motifs. At the end, 570 proteins were selected and entered the still very labor intensive screening phase. Over the last few years, our laboratories have been trying to move to more selective strategies. Our ultimate goal, we like to refer to as the “Holy Grail of Vaccinology,” is to identify protective antigens by “simply” scanning the genome sequence of any given pathogen, thus avoiding time consuming “wet science” and “move straight from genome to the clinic” (6).With this objective in mind, we have developed a series of proteomics-based protocols that, in combination with bioinformatics tools, have substantially reduced the number of antigens to be tested in the surrogate-of-protection assays (7, 8). In particular, we have recently described a three-technology strategy that allows to narrow the number of antigens to be tested in the animal models down to less than ten (9). However, this strategy still requires high throughput experimental activities. Therefore, the availability of in silico tools that selectively and accurately single out relevant categories of antigens among the complexity of pathogen components would greatly facilitate the vaccine discovery process.In the present work, we describe a new bioinformatics approach that brings an additional contribution to our “from genome to clinic” goal. The approach has been developed on the basis of the assumption that protective antigens are protective in that they have specific structural/functional features (“protective signatures”) that distinguish them from immunologically irrelevant pathogen components. These features have been identified by using existing databases and prediction tools, such as PFam and SMART. Our approach focuses on protein biological role rather than its localization: it is completely protein localization unbiased, and lead to the identification of both surface-exposed and secreted antigens (which are the majority in extracellular bacteria) as well as cytoplasmic protective antigens (for instance, antigens that elicit interferon γ producing CD4+ T cells, thus potentiating the killing activity of phagocytic cells toward intracellular pathogens). Should these assumptions be valid, PS could be identified if: (1) all known protective antigens are compiled to create what we refer to as “the Protectome space,” and (2) Protectome is subjected to computer-assisted scrutiny using selected tools. Once signatures are identified, novel protective antigens of a pathogen of interest should be identifiable by scanning its genome sequence in search for proteins that carry one or more protective signatures. A similar attempt has been reported (10), where the discrimination of protective antigens versus nonprotective antigens was tried using statistical methods based on amino acid compositional analysis and auto cross-covariance. This model was implemented in a server for the prediction of vaccine candidates, that is, Vaxijen (www.darrenflower.info/Vaxijen); however, the selection criteria applied are still too general leading to a list of candidates that include ca. 30% of the total genome ORFs very similarly to the number of antigens predicted by classical RV based on the presence of localization signals.Here we show that Protectome analysis unravels specific signatures embedded in protective antigens, most of them related to the biological role/function of the proteins. These signatures narrow down the candidate list to ca. 3% of the total ORFs content and can be exploited for protective antigen discovery. Indeed, the strategy was validated by demonstrating that well characterized vaccine components could be identified by scanning the genome sequence of the corresponding pathogens for the presence of the PS. Furthermore, when the approach was applied to Staphylococcus aureus and Streptococcus agalactiae (Group B Streptococcus, GBS) not only already known protective antigens were rediscovered, but also two new protective antigens were identified.