The impacts of agricultural payments on groundwater quality: Spatial analysis on the case of Slovenia

The European Common Agricultural Policy still follows its primary goals, i.e. quality food at affordable prices and a decent standard of living for farmers, fifty years after its adoption. Moreover, this policy adapts to the changing needs of society and the new challenges, mostly preservation of the environment, nature and biodiversity in rural areas. Although the Common Agricultural Policy receives the largest share of European budget, the funds are decreasing over time, especially direct payments, which aim to provide basic income support to farmers in the European Union. On the other hand, agri-environmental payments are gaining importance. Policy decision-makers should be interested in the question of impacts of growing eco-conditionality of agricultural spending. New insights would help them to be successful in achieving the goals of sustainable agriculture. The purpose of this paper is to estimate the impacts of production support payments and rural development payments on the quality of groundwater. We use the small EU country Slovenia as an example. The baseline indicators are the level of nitrates and pesticides in groundwater, while the impacts were estimated using spatial error model. The results show that direct payments, coupled subsidies and investment grants raise the level of pesticides in groundwater, but do not have any statistically significant impact on the level of nitrates in groundwater. Furthermore, we did not find any statistically significant effects of agri-environmental payments on decrease of groundwater pollution with nitrates. However, our findings revealed that agri-environmental payments are effective in reducing pesticides in groundwater, although only to a limited extent. These results imply a problem of insufficient targeting of agri-environmental measures on the one hand, and suggest that greening of direct payments is necessary and entirely justified.     

Modelling HIV immune response and validation with clinical data

A system of ordinary differential equations is formulated to describe the pathogenesis of HIV infection, wherein certain features that have been shown to be important by recent experimental research are incorporated in the model. These include the role of CD4+memory cells that serve as a major reservoir of latently infected cells, a critical role for T-helper cells in the generation of CD8 memory cells capable of efficient recall response, and stimulation by antigens other than HIV. A stability analysis illustrates the capability of this model in admitting multiple locally asymptotically stable (locally a.s.) off-treatment equilibria. We show that this more biologically detailed model can exhibit the phenomenon of transient viremia experienced by some patients on therapy with viral load levels suppressed below the detection limit. We also show that the loss of CD4+T-cell help in the generation of CD8+memory cells leads to larger peak values for the viral load during transient viremia. Censored clinical data is used to obtain parameter estimates. We demonstrate that using a reduced set of 16 free parameters, obtained by fixing some parameters at their population averages, the model provides reasonable fits to the patient data and, moreover, that it exhibits good predictive capability. We further show that parameter values obtained for most clinical patients do not admit multiple locally a.s off-treatment equilibria. This suggests that treatment to move from a high viral load equilibrium state to an equilibrium state with a lower (or zero) viral load is not possible for these patients.     

Influences of temporal independence of data on modelling species distributions

Modelling species distributions has been widely used to understand present and future potential distributions of species, and can provide adaptation and mitigation information as references for conservation and management under climate change. However, various methods of data splitting to develop and validate functions of the models do not get enough attention, which may mislead the interpretation of predicted results. We used the Taiwanese endemic birds to test the influences of temporal independence of datasets on model performance and prediction. Training and testing data were considered to be independent if they were collected during different survey periods (1993–2004 and 2009–2010). The results indicated no significant differences of six model performance measures (AUC, kappa, TSS, accuracy, sensitivity, and specificity) among the combinations of training and testing datasets. Both species- and grid cell-based assessments differed significantly between predictions by the annual and pooled training data. We also found an average of 85.8% similarity for species presences and absences in different survey periods. The remaining dissimilarity was mostly caused by species observed in the late survey period but not in the early one. The method of data splitting, yielding training and testing data, is critical for resulting model species distributions. Even if similar model performance exists, different methods can lead to different species distributional maps. More attention needs to be given to this issue, especially when amplifying these models to project species distributions in a changing world.     

An integrated network analysis reveals that nitric oxide reductase prevents metabolic cycling of nitric oxide by Pseudomonas aeruginosa

Nitric oxide (NO) is a chemical weapon within the arsenal of immune cells, but is also generated endogenously by different bacteria. Pseudomonas aeruginosa are pathogens that contain an NO-generating nitrite (NO₂⁻) reductase (NirS), and NO has been shown to influence their virulence. Interestingly, P. aeruginosa also contain NO dioxygenase (Fhp) and nitrate (NO₃⁻) reductases, which together with NirS provide the potential for NO to be metabolically cycled (NO→NO₃⁻→NO₂⁻→NO). Deeper understanding of NO metabolism in P. aeruginosa will increase knowledge of its pathogenesis, and computational models have proven to be useful tools for the quantitative dissection of NO biochemical networks. Here we developed such a model for P. aeruginosa and confirmed its predictive accuracy with measurements of NO, O₂, NO₂⁻, and NO₃⁻ in mutant cultures devoid of Fhp or NorCB (NO reductase) activity. Using the model, we assessed whether NO was metabolically cycled in aerobic P. aeruginosa cultures. Calculated fluxes indicated a bottleneck at NO₃⁻, which was relieved upon O₂ depletion. As cell growth depleted dissolved O₂ levels, NO₃⁻ was converted to NO₂⁻ at near-stoichiometric levels, whereas NO₂⁻ consumption did not coincide with NO or NO₃⁻ accumulation. Assimilatory NO₂⁻ reductase (NirBD) or NorCB activity could have prevented NO cycling, and experiments with ΔnirB, ΔnirS, and ΔnorC showed that NorCB was responsible for loss of flux from the cycle. Collectively, this work provides a computational tool to analyze NO metabolism in P. aeruginosa, and establishes that P. aeruginosa use NorCB to prevent metabolic cycling of NO.     

Synthesis,Molecular Modeling,and Biological Evaluation of Novel Chiral Thiosemicarbazone Derivatives as Potent Anticancer Agents

A series of new chiral thiosemicarbazones derived from homochiral amines in both enantiomeric forms were synthesized and evaluated for their in vitro antiproliferative activity against A549 (human alveolar adenocarcinoma), MCF‐7 (human breast adenocarcinoma), HeLa (human cervical adenocarcinoma), and HGC‐27 (human stomach carcinoma) cell lines. Some of compounds showed inhibitory activities on the growth of cancer cell lines. Especially, compound 17b exhibited the most potent activity (IC₅₀ 4.6 μM) against HGC‐27 as compared with the reference compound, sindaxel (IC₅₀ 10.3 μM), and could be used as a lead compound to search new chiral thiosemicarbazone derivatives as antiproliferative agents. Chirality 27:177–188, 2015. © 2014 Wiley Periodicals, Inc.     

Effects of Organic Solvents on the Coupling Between ATP Hydrolysis and Sliding of Microtubules in Axonemes from Chlamydomonas Flagella

ABSTRACT. The effects of organic solvents on the ATPase activity and the sliding disintegration of axonemes from Chlamydomonas were investigated. The axonemal ATPase was markedly activated by methanol accompanying with marked inhibition of the sliding disintegration of axonemes. On the contrary, glycerol inhibited the ATPase activity without serious inhibition of the sliding disintegration. As far as the axonemes are not irreversibly denatured by extremely high concentration of solvents, the effects of solvents both on the ATPase and the ability of sliding are reversible. Therefore, the inhibition of sliding accompanied by the activation of ATPase is probably due to an inability to couple the hydrolysis of ATP to sliding between dynein and microtubule in the presence of methanol. The axonemal ATPase was less sensitive to vanadate inhibition after exposure to methanol. This indicates that methanol makes the dyneinADP.Pi complex unstable and increases product release. On the other hand, glycerol and ethylene glycol seem to stabilize the force generation responsible for the sliding through stabilizing the dynein.ADP.Pi complex.