Comparative study between two distinct methods for attenuation correction and the use of no-attenuation correction for the assessment of relative uptake of 99mTc-DMSA on pediatric patients

Introduction: Although relative uptake values aren’t the most important objective of a 99mTc-DMSA scan, they are important quantitative information. In most of the dynamic renal scintigraphies attenuation correction is essential if one wants to obtain a reliable result of the quantification process. Although in DMSA scans the absent of significant background and the lesser attenuation in pediatric patients, makes that this attenuation correction techniques are actually not applied. The geometric mean is the most common method, but that includes the acquisition of an anterior (extra) projection, which it is not acquired by a large number of NM departments. This method and the attenuation factors proposed by Tonnesen will be correlated with the absence of attenuation correction procedures. Material and Methods: Images from 20 individuals (aged 3 years +/- 2) were used and the two attenuation correction methods applied. The mean time of acquisition (time post DMSA administration) was 3.5 hours +/- 0.8h. Results: The absence of attenuation correction showed a good correlation with both attenuation methods (r=0.73 +/- 0.11) and the mean difference verified on the uptake values between the different methods were 4 +/- 3. The correlation was higher when the age was lower. The attenuation correction methods correlation was higher between them two than with the “no attenuation correction” method (r=0.82 +/- 0.8), and the mean differences of the uptake values were 2 +/- 2. Conclusion: The decision of not doing any kind of attenuation correction method can be justified by the minor differences verified on the relative kidney uptake values. Nevertheless, if it is recognized that there is a need for an accurate value of the relative kidney uptake, then an attenuation correction method should be used. Attenuation correction factors proposed by Tonnesen can be easily implemented and so become a practical and easy to implement alternative, namely when the anterior projection - needed for the geometric mean methodology – is not acquired.

Myoglobin-biomimetic electroactive materials made by surface molecular imprinting on silica beads and their use as ionophores in polymeric membranes for potentiometric transduction

Myoglobin (Mb) is among the cardiac biomarkers playing a major role in urgent diagnosis of cardiovascular diseases. Its monitoring in point-of-care is therefore fundamental. Pursuing this goal, a novel biomimetic ionophore for the potentiometric transduction of Mb is presented. It was synthesized by surface molecular imprinting (SMI) with the purpose of developing highly efficient sensor layers for near-stereochemical recognition of Mb. The template (Mb) was imprinted on a silane surface that was covalently attached to silica beads by means of self-assembled monolayers. First the silica was modified with an external layer of aldehyde groups. Then, Mb was attached by reaction with its amine groups (on the external surface) and subsequent formation of imine bonds. The vacant places surrounding Mb were filled by polymerization of the silane monomers 3-aminopropyltrimethoxysilane (APTMS) and propyltrimethoxysilane (PTMS). Finally, the template was removed by imine cleavage after treatment with oxalic acid. The results materials were finely dispersed in plasticized PVC selective membranes and used as ionophores in potentiometric transduction. The best analytical features were found in HEPES buffer of pH 4. Under this condition, the limits of detection were of 1.3 × 10−6 mol/L for a linear response after 8.0 × 10−7 mol/L with an anionic slope of −65.9 mV/decade. The imprinting effect was tested by preparing non-imprinted (NI) particles and employing these materials as ionophores. The resulting membranes showed no ability to detect Mb. Good selectivity was observed towards creatinine, sacarose, fructose, galactose, sodium glutamate, and alanine. The analytical application was conducted successfully and showed accurate and precise results.

Effects of treatment, awareness and condom use in a coinfection model for HIV and HCV in MSM

We develop a new a coinfection model for hepatitis C virus (HCV) and the human immunodeficiency virus (HIV). We consider treatment for both diseases, screening, unawareness and awareness of HIV infection, and the use of condoms. We study the local stability of the disease-free equilibria for the full model and for the two submodels (HCV only and HIV only submodels). We sketch bifurcation diagrams for different parameters, such as the probabilities that a contact will result in a HIV or an HCV infection. We present numerical simulations of the full model where the HIV, HCV and double endemic equilibria can be observed. We also show numerically the qualitative changes of the dynamical behavior of the full model for variation of relevant parameters. We extrapolate the results from the model for actual measures that could be implemented in order to reduce the number of infected individuals.

Access and use of european information: a comparative analysis

This paper presents some results of a survey on access to European information among a group of 234 users of 55 European Documentation Centres (EDCs), from 21 European Union (EU) Member-States. The findings of the questionnaire made to 88 EDCs' managers, from 26 EU Member-States, will also be analyse. Two different points of view regarding issues related to reasons to access European information, the valued aspects during that access and the use of European databases will be compare.

Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.