Methods and Results. Introduction The SWASH+ program has conducted limited research into spending and budgeting practices for WASH systems support at primary schools. This study is intended to fill this research gap. We will explore the recurrent costs for maintaining school WASH systems, as well as examine spending and budgeting practices for WASH systems repair, maintenance, and operations in greater detail. Data collection was carried out at primary schools in Kenya that participate in SWASH+ program interventions due to the strong relationships between school head teachers and SWASH+ staff and the potential to collect extensive school-level information. Study instruments and methods were pilot tested at three SWASH+ primary schools in the Kisumu area. Results from the pilot tests were used to make changes to the instruments and methods, which were implemented prior to data collection at sample schools. Research Design The methods and materials used to collect data for this study were developed from January 2010 to May 2010. The research design was developed through collaboration with SWASH+ project partners at Emory University’s Center for Global Safe Water and CARE Kenya. Preliminary information-gathering was conducted through literature reviews and discussions with SWASH+ partners.
Methods and Results. The time-course of acute inflammatory cell infiltration was quantified by FACS analysis of enzymatically digested hearts of FVB mice (n=12) following LAD ligation. Mac-1+Gr-1high neutrophil infiltration peaked at day 4. BMCs were harvested from transgenic FVB mice expressing firefly luciferase (Fluc) and green fluorescent protein (GFP). Afterwards, 2.5x106 BMCs were injected into the left ventricle of wild-type FVB mice either immediately (Acute BMC) or 7 days (Sub-acute BMC) after MI, or after a sham procedure (n=8 per group). In vivo bioluminescence imaging (BLI) showed an early signal increase in the Acute BMC group at day 7, followed by a trend towards improved BMC survival in the Sub-acute BMC group that persisted until the BLI signal reached background levels after 42 days. Compared to controls (MI + saline injection), echocardiography showed a significant preservation of fractional shortening at 4 weeks (Acute BMC vs saline; P<0.01) and 6 weeks (both BMC groups vs saline; P<0.05), but no significant differences between the two BMC groups. FACS analysis of BMC injected hearts at day 7 revealed that GFP+ BMCs expressed hematopoietic (CD45, Mac-1, Gr-1) markers, minimal progenitor (Sca-1, c-kit), and no endothelial (CD133, Flk-1) or cardiac (Trop-T) cell markers.
Methods and Results. A complementary approach using different spectroscopic techs has been used to know whether the system is able to interact with Aβ42 and to inhibit its uncontrolled aggregation towards Aβ42 insoluble fibrils. ThT and CD kinetics studies provide us with the evidence that Zn-Porph inhibits the amyloid proto-fibrils and fibrils formation of Aβ42. We also addressed the question whether the Zn-Porph could also inhibit the formation of the neurotoxic LMWs of Aβ40. We deemed that the use of in vitro models of Aβ40 peptide, a more soluble and less aggregation prone than Aβ42, might allow us to better follow at what stage the Zn-Porph could intervene in the oligomerization process over the timescale of our experiments. For the first time, we combined electrospray ionization ion mobility mass spectrometry (ESI-IM-MS) with multivariate statistical analysis (MVA) to compare the IM-MS profiles of multiple samples and to reveal a subset of statistically significant early-stage species of Aβ40 whose formation was inhibited in the samples containing Zn-Porph. The IMMS-MVA approach revealed that the Zn-Porph alters the distributions of both monomeric and dimeric conformers of Aβ40 inhibiting their formation at the early stage of the aggregation pathway.
Methods and Results. The parameters for measuring the quality level and richness in samples and data of the European biobanks have been defined by the WP2 working group (Table 1.). The assessment tool (Biobank questionnaire Table 2., and the WP6 D6.2 pre-‐analytics evaluation tool, delivered in M18) is built up on the needs of biobankers, and takes into account Quality Management System in general, pre-‐ examination processes, performance evaluation (Product specification report). The results are also reported to in the BBMRI-‐XXXX Work Programme 2016 (the Work Stream 2 Quality, of the 2016 Work Programme of BBMRI-‐XXXX, Work Stream 2.1: Molecular In-‐vitro Diagnostic Examination of CEN/TC and Work Stream 2.2 Self Assessment Tool for Biobanks)2. The work takes into account the documents and guidelines specifically referred to in the BBMRI-‐XXXX Partner Charter1,OECD best practice guidelines for Biological Resource Centres and WHO/IARC guidelines for biological resource centres for cancer research, and additional National and International Guidelines (NFS 96-‐900 Certification des Centres de Resources Biologiques, ISBER Best practices for Repositories, ISO 9001:2015 Quality management systems requirements, ISO 15189:2012 Medical laboratories – Requirements for quality and competence, ISO 17025:2005 General requirements for the competence of testing and calibration laboratories, ISO 19011:2011 Guidelines for auditing management systems)3. All parameters for compliance with the BBMRI-‐XXXX Partner Charter1 have been applied primacy, access policy, data protection and management policy, informed consent, infrastructure and management, quality management, charges. Already available tools produced by the Italian Node (questionnaire XXXXX.xx) and by the Austrian Node (Pre-‐An Tool)4 were also analysed, with the aim of a) building a self-‐evaluation questionnaire, taking into account all parameters relevant to the quality management of biobanks; b) defining a standardized method of evaluation, by giving a score to each parameter and by weighing the items under evaluation on the basis of their respective importance; c) providing the self-‐evaluation tool to the National Nodes, in order to adapt it to specific requirements; d) assessing the efficacy of this evaluation system through on-‐site audits of biobanks. In order to validate the information gained through the questionnaire/ on-‐line self assessment tool for the biobanks, on-‐site visits to biobanks by members of the...
Methods and Results. E3L.CETP mice were fed a cholesterol-rich without drugs or with torcetrapib (12 mg/kg/day), atorvastatin (2.8 mg/kg/day) or both for 14 weeks. Torcetrapib decreased CETP activity both in the absence and presence of atorvastatin (-74% and -73% respectively, P<0.001). Torcetrapib decreased plasma cholesterol (-20%, P<0.01), albeit to a lesser extent than atorvastatin (- 42%, P<0.001) or the combination of torcetrapib and atorvastatin (-40%, P<0.001). Torcetrapib increased HDL-cholesterol in the absence (+30%) and in the presence (+34%) of atorvastatin. Torcetrapib and atorvastatin alone both reduced atherosclerotic lesion size (-43% and -46%, P<0.05), but combination therapy did not reduce atherosclerosis as compared to atorvastatin alone. Remarkably, as compared to atorvastatin, torcetrapib induced enhanced monocyte recruitment and expression of monocyte chemoattractant protein-1 and resulted in lesions of a more inflammatory phenotype, as reflected by an increased macrophage content and reduced collagen content.
Methods and Results. Two studies were conducted based on a collection of 26 data sharing agreements. Study 1 was a keyword extraction and term proximity analysis. Word counts, common words (or phrases) appearing within a selected range of terms, such as “personally identifiable data,” “personally identifiable information,” “disclosure,” “data restriction,” and “privacy” were tallied. Study 2 was a content analysis of the licenses, which involved parsing concepts, confirming high-‐level classes, sub-‐classes, and attributes. The results include 6 high level classes, 15 mid-‐level sub-‐classes, and over 90 lower-‐level specific attributes, a portion of which can help to expeditiously support the automatic development of data sharing agreements.
Methods and Results. In particular, we have presented how the Modelling Computational Platform has provided realistic scenarios of epidemic spreading during the Xxxx emergency. As of mid-2016, a widespread epidemic of Xxxx fever, caused by the Xxxx virus (ZIKV), was on-going in the Americas, the Pacific and Southeast Asia. The outbreak began in early 2015 in Brazil, and then spread to other parts of South and North America also affecting several islands in the Pacific, and Southeast Asia. In January 2016, the World Health Organization (WHO) said the virus was likely to spread throughout most of the Americas by the end of the year. In November 2016, the WHO Director-General declared the end of the Public Health Emergency of International Concern regarding microcephaly, other neurological disorders and Xxxx virus. The Modelling Computational Platform results published in the page xxxx://xxx.xxxx-xxxxx.org/index.html have been illustrated to the Public Health officials who could find detailed visualizations comparing the following epidemic scenarios:
Methods and Results
