35 resultados para profile likelihood
Resumo:
Striatal adenosine A2A receptors (A2ARs) are highly expressed in medium spiny neurons (MSNs) of the indirect efferent pathway, where they heteromerize with dopamine D2 receptors (D2Rs). A2ARs are also localized presynaptically in cortico-striatal glutamatergic terminals contacting MSNs of the direct efferent pathway, where they heteromerize with adenosine A1 receptors (A1Rs). It has been hypothesized that postsynaptic A2AR antagonists should be useful in Parkinson's disease, while presynaptic A2AR antagonists could be beneficial in dyskinetic disorders, such as Huntington's disease, obsessive-compulsive disorders and drug addiction. The aim or this work was to determine whether selective A2AR antagonists may be subdivided according to a preferential pre- versus postsynaptic mechanism of action. The potency at blocking the motor output and striatal glutamate release induced by cortical electrical stimulation and the potency at inducing locomotor activation were used as in vivo measures of pre- and postsynaptic activities, respectively. SCH-442416 and KW-6002 showed a significant preferential pre- and postsynaptic profile, respectively, while the other tested compounds (MSX-2, SCH-420814, ZM-241385 and SCH-58261) showed no clear preference. Radioligand-binding experiments were performed in cells expressing A2AR-D2R and A1R-A2AR heteromers to determine possible differences in the affinity of these compounds for different A2AR heteromers. Heteromerization played a key role in the presynaptic profile of SCH-442416, since it bound with much less affinity to A2AR when co-expressed with D2R than with A1R. KW-6002 showed the best relative affinity for A2AR co-expressed with D2R than co-expressed with A1R, which can at least partially explain the postsynaptic profile of this compound. Also, the in vitro pharmacological profile of MSX-2, SCH-420814, ZM-241385 and SCH-58261 was is in accordance with their mixed pre- and postsynaptic profile. On the basis of their preferential pre- versus postsynaptic actions, SCH-442416 and KW-6002 may be used as lead compounds to obtain more effective antidyskinetic and antiparkinsonian compounds, respectively.
Resumo:
OBJECTIVES: Polypharmacy is one of the main management issues in public health policies because of its financial impact and the increasing number of people involved. The polymedicated population according to their demographic and therapeutic profile and the cost for the public healthcare system were characterised. DESIGN: Cross-sectional study. SETTING: Primary healthcare in Barcelona Health Region, Catalonia, Spain (5 105 551 inhabitants registered). PARTICIPANTS: All insured polymedicated patients. Polymedicated patients were those with a consumption of ≥16 drugs/month. MAIN OUTCOMES MEASURES: The study variables were related to age, gender and medication intake obtained from the 2008 census and records of prescriptions dispensed in pharmacies and charged to the public health system. RESULTS: There were 36 880 polymedicated patients (women: 64.2%; average age: 74.5±10.9 years). The total number of prescriptions billed in 2008 was 2 266 830 (2 272 920 total package units). The most polymedicated group (up to 40% of the total prescriptions) was patients between 75 and 84 years old. The average number of prescriptions billed monthly per patient was 32±2, with an average cost of 452.7±27.5. The total cost of those prescriptions corresponded to 2% of the drug expenditure in Catalonia. The groups N, C, A, R and M represented 71.4% of the total number of drug package units dispensed to polymedicated patients. Great variability was found between the medication profiles of men and women, and between age groups; greater discrepancies were found in paediatric patients (5-14 years) and the elderly (≥65 years). CONCLUSIONS: This study provides essential information to take steps towards rational drug use and a structured approach in the polymedicated population in primary healthcare.
Resumo:
This article examines the participation of Spanish older people in formal, non-formal and informal learning activities and presents a profile of participants in each kind of learning activity. We used data from a nationally representative sample of Spanish people between 60 and 75 years old (n = 4,703). The data were extracted from the 2007 Encuesta sobre la Participación de la Población Adulta en Actividades de Aprendizaje (EADA, Survey on Adult Population Involvement in Learning Activities). Overall, only 22.8 % of the sample participated in a learning activity. However, there was wide variation in the participation rates for the different types of activity. Informal activities were far more common than formal ones. Multivariate logistic regression indicated that education level and involvement in social and cultural activities were associated with likelihood of participating, regardless of the type of learning activity. When these variables were taken into account, age did not predict decreasing participation, at least in non-formal and informal activities. Implications for further research, future trends and policies to promote older adult education are discussed.
Resumo:
Marketing scholars have suggested a need for more empirical research on consumer response to malls, in order to have a better understanding of the variables that explain the behavior of the consumers. The segmentation methodology CHAID (Chi-square automatic interaction detection) was used in order to identify the profiles of consumers with regard to their activities at malls, on the basis of socio-demographic variables and behavioral variables (how and with whom they go to the malls). A sample of 790 subjects answered an online questionnaire. The CHAID analysis of the results was used to identify the profiles of consumers with regard to their activities at malls. In the set of variables analyzed the transport used in order to go shopping and the frequency of visits to centers are the main predictors of behavior in malls. The results provide guidelines for the development of effective strategies to attract consumers to malls and retain them there.
Resumo:
Standard indirect Inference (II) estimators take a given finite-dimensional statistic, Z_{n} , and then estimate the parameters by matching the sample statistic with the model-implied population moment. We here propose a novel estimation method that utilizes all available information contained in the distribution of Z_{n} , not just its first moment. This is done by computing the likelihood of Z_{n}, and then estimating the parameters by either maximizing the likelihood or computing the posterior mean for a given prior of the parameters. These are referred to as the maximum indirect likelihood (MIL) and Bayesian Indirect Likelihood (BIL) estimators, respectively. We show that the IL estimators are first-order equivalent to the corresponding moment-based II estimator that employs the optimal weighting matrix. However, due to higher-order features of Z_{n} , the IL estimators are higher order efficient relative to the standard II estimator. The likelihood of Z_{n} will in general be unknown and so simulated versions of IL estimators are developed. Monte Carlo results for a structural auction model and a DSGE model show that the proposed estimators indeed have attractive finite sample properties.