New Porous Heterostructures Based on Organo-Modified Graphene Oxide for CO(2)Capture

In this work, we report on a facile and rapid synthetic procedure to create highly porous heterostructures with tailored properties through the silylation of organically modified graphene oxide. Three silica precursors with various structural characteristics (comprising alkyl or phenyl groups) were employed to create high-yield silica networks as pillars between the organo-modified graphene oxide layers. The removal of organic molecules through the thermal decomposition generates porous heterostructures with very high surface areas (>= 500 m(2)/g), which are very attractive for potential use in diverse applications such as catalysis, adsorption and as fillers in polymer nanocomposites. The final hybrid products were characterized by X-ray diffraction, Fourier transform infrared and X-ray photoelectron spectroscopies, thermogravimetric analysis, scanning electron microscopy and porosity measurements. As proof of principle, the porous heterostructure with the maximum surface area was chosen for investigating its CO(2)adsorption properties

Toward an Open-Access Global Database for Mapping, Control, and Surveillance of Neglected Tropical Diseases

Abstract Background: After many years of general neglect, interest has grown and efforts came under way for the mapping, control, surveillance, and eventual elimination of neglected tropical diseases (NTDs). Disease risk estimates are a key feature to target control interventions, and serve as a benchmark for monitoring and evaluation. What is currently missing is a georeferenced global database for NTDs providing open-access to the available survey data that is constantly updated and can be utilized by researchers and disease control managers to support other relevant stakeholders. We describe the steps taken toward the development of such a database that can be employed for spatial disease risk modeling and control of NTDs

Toward an Open-Access Global Database for Mapping, Control, and Surveillance of Neglected Tropical Diseases

There is growing interest in the scientific community, health ministries, and other organizations to control and eventually eliminate neglected tropical diseases (NTDs). Control efforts require reliable maps of NTD distribution estimated from appropriate models and survey data on the number of infected people among those examined at a given location. This kind of data is often available in the literature as part of epidemiological studies. However, an open-access database compiling location-specific survey data does not yet exist. We address this problem through a systematic literature review, along with contacting ministries of health, and research institutions to obtain disease data, including details on diagnostic techniques, demographic characteristics of the surveyed individuals, and geographical coordinates. All data were entered into a database which is freely accessible via the Internet (http://www.gntd.org). In contrast to similar efforts of the Global Atlas of Helminth Infections (GAHI) project, the survey data are not only displayed in form of maps but all information can be browsed, based on different search criteria, and downloaded as Excel files for further analyses. At the beginning of 2011, the database included over 12,000 survey locations for schistosomiasis across Africa, and it is continuously updated to cover other NTDs globally

Malaria ecotypes and stratification

To deal with the variability of malaria, control programmes need to stratify their malaria problem into a number of smaller units. Such stratification may be based on the epidemiology of malaria or on its determinants such as ecology. An ecotype classification was developed by the World Health Organization (WHO) around 1990, and it is time to assess its usefulness for current malaria control as well as for malaria modelling on the basis of published research. Journal and grey literature was searched for articles on malaria or Anopheles combined with ecology or stratification. It was found that all malaria in the world today could be assigned to one or more of the following ecotypes: savanna, plains and valleys; forest and forest fringe; foothill; mountain fringe and northern and southern fringes; desert fringe; coastal and urban. However, some areas are in transitional or mixed zones; furthermore, the implications of any ecotype depend on the biogeographical region, sometimes subregion, and finally, the knowledge on physiography needs to be supplemented by local information on natural, anthropic and health system processes including malaria control. Ecotyping can therefore not be seen as a shortcut to determine control interventions, but rather as a framework to supplement available epidemiological and entomological data so as to assess malaria situations at the local level, think through the particular risks and opportunities and reinforce intersectoral action. With these caveats, it does however emerge that several ecotypic distinctions are well defined and have relatively constant implications for control within certain biogeographic regions. Forest environments in the Indo-malay and the Neotropics are, with a few exceptions, associated with much higher malaria risk than in adjacent areas; the vectors are difficult to control, and the anthropic factors also often converge to impose constraints. Urban malaria in Africa is associated with lower risk than savanna malaria; larval control may be considered though its role is not so far well established. In contrast, urban malaria in the Indian subcontinent is associated with higher risks than most adjacent rural areas, and larval control has a definite, though not exclusive, role. Simulation modelling of cost-effectiveness of malaria control strategies in different scenarios should prioritize ecotypes where malaria control encounters serious technical problems. Further field research on malaria and ecology should be interdisciplinary, especially with geography, and pay more attention to juxtapositions and to anthropic elements, especially migratio

Flow-chart showing the steps used to assemble the GNTD database.

<p>1. PubMed <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-PubMed1" target="_blank">[24]</a>, ISI Web of Knowledge <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-ISI1" target="_blank">[25]</a>, African Journal Online (AJOL) <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-African1" target="_blank">[26]</a>, Institut de Recherche pour le Développement (IRD)-resources documentaries <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-IRD1" target="_blank">[28]</a>, WHO library archive <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-WHO2" target="_blank">[27]</a>, Doumenge et al. <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001404#pntd.0001404-Doumenge1" target="_blank">[17]</a>; 2. Dissertations and theses in local universities or public health departments, ministry of health reports, other reports and personal communication. 3. Proforma and MySQL database include: (i) data source (authors); (ii) document type; (iii) location of the survey; (iv) area information (rural or urban); (v) coordinates (lat long in decimal degrees); (vi) method of the sample recruitment and diagnostic technique; (vii) description of survey (community-, school- or hospital-based); (viii) date of survey (month/year); and (ix) prevalence information (number of subjects examined and positive by age group and parasite species).</p