The Use of LNG as a Marine Fuel: The International Regulatory Framework

While shipping is a carbon efficient transport mode, given that roughly 90% of the world trade is carried by ships, the negative impact of shipping on human health and the natural environment is significant. One of the attempts being made by the shipping industry to reduce its environmental impact is to use liquefied natural gas (LNG) as a marine fuel. This article examines the regulatory legal regime in relation to the use of LNG as marine fuel and highlights the areas where further development is necessary.     

Economic evaluation of water loss saving due to the biological control of water hyacinth at New Year’s Dam,Eastern Cape province,South Africa

Water hyacinth Eichhornia crassipes is considered the most damaging aquatic weed in the world. However, few studies have quantified the impact of this weed economically and ecologically, and even fewer studies have quantified the benefits of its control. This paper focuses on water loss saving as the benefit derived from biological control of this plant between 1990 and 2013 at New Year’s Dam, Alicedale, Eastern Cape, South Africa. Estimates of water loss due to evapotranspiration from water hyacinth vary significantly; therefore, the study used three different rates, high, medium and low. A conservative raw agriculture value of R 0.26 per m³ was used to calculate the benefits derived by the water saved. The present benefit and cost values were determined using 10% and 5% discount rates. The benefit/cost ratio at the low evapotranspiration rate was less than one, implying that biological control was not economically viable but, at the higher evapotranspiration rates, the return justified the costs of biological control. However, at the marginal value product of water, the inclusion of the costs of damage to infrastructure, or the adverse effects of water hyacinth on biodiversity, would justify the use of biological control, even at the low transpiration rate.     

Mortality and Morbidity of Urban Road Traffic Crashes in Africa: Capture-Recapture Estimates in Bamako,Mali, 2012

Background

Low- and middle-income countries are currently facing the massive public health challenge of road traffic injuries. The lack of effective surveillance systems hinders proper assessment of epidemiologic status and intervention priorities. The objective of our study was to estimate the mortality and morbidity attributable to road crashes in Bamako, Mali using the capture-recapture method.

Methods

During the 1 January, 2012–31 April, 2012 period, we collected data on road traffic crashes from the road accident registers of the police forces of Bamako, Mali on the one hand, and from a register kept by health facilities in the same area. An automatic, then manual matching procedure was performed to find pairs of records related to the same crash victims. The number of victims and the number of fatalities were estimated by the capture-recapture method using the Chapman estimator.

Results

The health facility and the police registries included 3587 and 1432 records, respectively. The matching procedure identified 603 common records, 31 of which were fatalities. The annual incidence estimate for road victims was 1038 in 100 000 and the annual incidence estimate for road fatalities was 12 in 100 000. Victims from both sources were more likely to be male, in the 15–34 age group, and almost half of all injured road users and two in three fatalities were using motorized two-wheelers. One victim out of five was a pedestrian.

Conclusion

Our estimates are in line with available literature data from low-income countries. While more cases were reported by health facilities than by police forces, we believe that an effective surveillance system should not be based solely on medical reports as much would be missing as regards the crash circumstances and characteristics.     

Spatiotemporal Evolution of Ebola Virus Disease at Sub-National Level during the 2014 West Africa Epidemic: Model Scrutiny and Data Meagreness

Background

The Ebola outbreak in West Africa has infected at least 27,443 individuals and killed 11,207, based on data until 24 June, 2015, released by the World Health Organization (WHO). This outbreak has been characterised by extensive geographic spread across the affected countries Guinea, Liberia and Sierra Leone, and by localized hotspots within these countries. The rapid recognition and quantitative assessment of localised areas of higher transmission can inform the optimal deployment of public health resources.

Methods

A variety of mathematical models have been used to estimate the evolution of this epidemic, and some have pointed out the importance of the spatial heterogeneity apparent from incidence maps. However, little is known about the district-level transmission. Given that many response decisions are taken at sub-national level, the current study aimed to investigate the spatial heterogeneity by using a different modelling framework, built on publicly available data at district level. Furthermore, we assessed whether this model could quantify the effect of intervention measures and provide predictions at a local level to guide public health action. We used a two-stage modelling approach: a) a flexible spatiotemporal growth model across all affected districts and b) a deterministic SEIR compartmental model per district whenever deemed appropriate.

Findings

Our estimates show substantial differences in the evolution of the outbreak in the various regions of Guinea, Liberia and Sierra Leone, illustrating the importance of monitoring the outbreak at district level. We also provide an estimate of the time-dependent district-specific effective reproduction number, as a quantitative measure to compare transmission between different districts and give input for informed decisions on control measures and resource allocation. Prediction and assessing the impact of control measures proved to be difficult without more accurate data. In conclusion, this study provides us a useful tool at district level for public health, and illustrates the importance of collecting and sharing data.     

The biochemistry of drug metabolism--an introduction: Part 2. Redox reactions and their enzymes

This review continues a general presentation of the metabolism of drugs and other xenobiotics started in a recent issue of Chemistry & Biodiversity. This Part 2 presents the numerous oxidoreductases involved, their nomenclature, relevant biochemical properties, catalytic mechanisms, and the very diverse reactions they catalyze. Many medicinally, environmentally, and toxicologically relevant examples are presented and discussed. Cytochromes P450 occupy a majority of the pages of Part 2, but a large number of relevant oxidoreductases are also considered, e.g., flavin-containing monooxygenases, amine oxidases, molybdenum hydroxylases, peroxidases, and the innumerable dehydrogenases/reductases.     

Variation, natural selection, and information content--a simulation

In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms that propel biological evolution. Variation implies changes in the gene pool of a population, enlarging the genetic variability from which natural selection can choose. But in the absence of natural selection, variation causes dissipation and randomization. Natural selection, in contrast, constrains this variability by decreasing the survival and fertility of the less-adapted organisms. The objective of this study is to propose a highly simplified simulation of variation and natural selection, and to relate the observed evolutionary changes in a population to its information content. The model involves an imaginary population of individuals. A quantifiable character allows the individuals to be categorized into bins. The distribution of bins (a histogram) was assumed to be Gaussian. The content of each bin was calculated after one to twelve cycles, each cycle spanning N generations (N being undefined). In a first study, selection was simulated in the absence of variation. This was modeled by assuming a differential fertility factor F that increased linearly from the lower bins (F<1.00) to the higher bins (F>1.00). The fertility factor was applied as a multiplication factor during each cycle. Several ranges of fertility were investigated. The resulting histograms became skewed to the right. In a second study, variation was simulated in the absence of selection. This was modeled by assuming that during each cycle each bin lost a fixed percentage of its content (variation factor Y) to its two adjacent bins. The resulting histograms became broader and flatter, while retaining their bilateral symmetry. Different values of Y were monitored. In a third study, various values of F and Y were combined. Our model allows the straightforward application of Shannon's equation and the calculation of a Shannon-entropy (SE) values for each histogram. Natural selection was, thus, shown to result in a progressive decrease in SE as a function of F. In other words, natural selection, when acting alone, progressively increased the information content of the population. In contrast, variation resulted in a progressive increase in SE as a function of Y. In other words, variation acting alone progressively decreased the information content of a population. When both factors, F and Y, were applied simultaneously, their relative weight determined the progressive change in SE.     

In silico strategies to couple production of bioethanol with growth in cyanobacteria

Cyanobacteria have been considered as promising candidates for sustainable bioproduction from inexpensive raw materials, as they grow on light, carbon dioxide, and minimal inorganic nutrients. In this study, we present a genome-scale metabolic network model for Synechocystis sp. PCC 6803 and study the optimal design of the strain for ethanol production by using a mixed integer linear problem reformulation of a bilevel programming problem that identifies gene knockouts which lead to coupling between growth and product synthesis. Five mutants were found, where the in silico model predicts coupling between biomass growth and ethanol production in photoautotrophic conditions. The best mutant gives an in silico ethanol production of 1.054 mmol·gDW ⁻¹·h ⁻¹.     

Rapid modification of bacterial artificial chromosomes by ET-recombination

We present a method to modify bacterial artificial chromosomes (BACs) resident in their host strain. The method is based on homologous recombination by ET-cloning. We have successfully modified BACs at two distinct loci by recombination with a PCR product containing homology arms of 50 nt. The procedure we describe here is rapid, was found to work with high efficiency and should be applicable to any BAC modification desired.     

Screening of non-alkaloidal natural compounds as acetylcholinesterase inhibitors

Acetylcholinesterase (AChE) inhibitors are currently the only approved therapy for the treatment of Alzheimer's disease, only a limited number of drugs are commercially available. A library of non-alkaloidal natural compounds was investigated. To this end, a convenient microtitre plate method for assaying AChE inhibition, which allows a complete kinetic analysis of AChE inhibitors, was developed. Seven active compounds with Ki values in the micromolar range were identified, six of which were xanthones. This is the first report that a promising potential for AChE inhibition exists in such non-nitrogenous natural compounds. Furthermore, four xanthones among these xanthones had already been described as monoamine oxidase (MAO) inhibitors, making then dual AChE/MAO inhibitors of great interest.