989 resultados para behavioral models
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BACKGROUND: General anesthetics (GA) are well known for the ability to induce a state of reversible loss of consciousness and unresponsiveness to painful stimuli. However, evidence from animal models and clinical studies show that GA exposure may induce behavioral changes beyond acute effects. Most research and concerns are focused on changes in cognition and memory. METHODS: We will look at effects of GA on behavior that is mediated by the dopaminergic system. RESULTS: Pharmacological resemblance of GA with drugs of abuse, and the complexity and importance of dopaminergic systems in both reward seeking and addictive illnesses make us believe that it deserves an overview about what is already known and what matters to us as healthcare workers and specifically as anesthesiologists. CONCLUSION: A review of available evidence strongly suggests that there may be a link between the effects of GA on the brain and substance abuse, partly explained by their influence on the dopaminergic system.
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Author's personal copy
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The aim of this study was to determine if mycobacterial lineages affect infection risk, clustering, and disease progression among Mycobacterium tuberculosis cases in The Netherlands. Multivariate negative binomial regression models adjusted for patient-related factors and stratified by patient ethnicity were used to determine the association between phylogenetic lineages and infectivity (mean number of positive contacts around each patient) and clustering (as defined by number of secondary cases within 2 years after diagnosis of an index case sharing the same fingerprint) indices. An estimate of progression to disease by each risk factor was calculated as a bootstrapped risk ratio of the clustering index by the infectivity index. Compared to the Euro-American reference, Mycobacterium africanum showed significantly lower infectivity and clustering indices in the foreign-born population, while Mycobacterium bovis showed significantly lower infectivity and clustering indices in the native population. Significantly lower infectivity was also observed for the East African Indian lineage in the foreign-born population. Smear positivity was a significant risk factor for increased infectivity and increased clustering. Estimates of progression to disease were significantly associated with age, sputum-smear status, and behavioral risk factors, such as alcohol and intravenous drug abuse, but not with phylogenetic lineages. In conclusion, we found evidence of a bacteriological factor influencing indicators of a strain's transmissibility, namely, a decreased ability to infect and a lower clustering index in ancient phylogenetic lineages compared to their modern counterparts. Confirmation of these findings via follow-up studies using tuberculin skin test conversion data should have important implications on M. tuberculosis control efforts.
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Do stars govern our actions? Astrocyte involvement in rodent behavior
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Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.
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"Series: Solid mechanics and its applications, vol. 226"
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"Series: Solid mechanics and its applications, vol. 226"
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"Series: Solid mechanics and its applications, vol. 226"
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"Series: Solid mechanics and its applications, vol. 226"
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"A workshop within the 19th International Conference on Applications and Theory of Petri Nets - ICATPN’1998"
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This study aims to (a) identify and profile groups of infants according to their behavioral and physiological characteristics, considering their neurobehavioral organization, social withdrawal behavior, and endocrine reactivity to stress, and to (b) analyze group differences in the quality of mother–infant interaction. Ninety seven 8-week-old infants were examined using the Neonatal Behavioral Assessment Scale and the Alarm Distress Baby Scale. Cortisol levels were measured both before and after routine inoculation between 8 and 12 weeks. At 12 to 16 weeks mother–infant interaction was assessed using the Global Rating Scales of Mother–Infant Interaction. Three groups of infants were identified: (a) ‘‘withdrawn’’; (b) ‘‘extroverted’’; (c) ‘‘underaroused.’’ Differences between them were found regarding both infant and mother behaviors in the interaction and the overall quality of mother–infant interaction. The identification of behavioral and physiological profiles in infants is an important step in the study of developmental pathways.
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Background: Maternal depression is a worldwide phenomenon that has been linked to adverse developmental outcomes in neonates. Aims: To study the effect of antenatal depression (during the third trimester of pregnancy) on neonate behavior, preference, and habituation to both the mother and a stranger’s face/voice. To analyze mother’s depression at childbirth as a potential mediator or moderator of the relationship between antenatal depression and neonate behavioral development. Method: A sample of 110 pregnant women was divided in 2 groups according to their scores on the Edinburgh Postnatal Depression Scale during pregnancy (EPDS; ≥10, depressed; <10, non-depressed). In the first 5 days after birth, neonatal performance on the Neonatal Behavioral Assessment Scale (NBAS) and in the ‘Preference and habituation to the mother’s face/voice versus stranger’ paradigm was assessed; each mother filled out an EPDS. Results: Neonates of depressed pregnant women, achieved lower scores on the NBASs (regulation of state, range of state, and habituation); did not show a visual/auditory preference for the mother’s face/voice; required more trials to become habituated to the mother’s face/voice; and showed a higher visual/auditory preference for the stranger’s face/voice after habituation compared to neonates of non-depressed pregnant women. Depression at childbirth does not contribute to the effect of antenatal depression on neonatal behavioral development. Conclusion: Depression even before childbirth compromises the neonatal behavioral development. Depression is a relevant issue and should be addressed as a routine part of prenatal health care.
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Background: The Neonatal Behavioral Assessment Scale (NBAS, Brazelton & Nugent, 1995) is an instrument conceived to observe the neonatal neurobehavior. Data analysis is usually performed by organizing items into groups. The most widely used data reduction for the NBAS was developed by Lester, Als, and Brazelton (1982). Objective: Examine the psychometric properties of the NBAS items in a sample of 213 Portuguese infants. Method: The NBAS was performed in the first week of infant life (3 days±2) and in the seventh week of life (52 days±5). Results: Principal component analyses yielded a solution of four components explaining 55.13% of total variance. Construct validity was supported by better neurobehavioral performance of 7-week-old infants compared with 1-week-old infants. Conclusion: Changes in the NBAS structure for the Portuguese sample are suggested compared to Lester factors in order to reach better internal consistency of the scale.
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The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.
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Tese de Doutoramento em Psicologia Aplicada.