Can the dopaminergic-related effects of general anesthetics be linked to mechanisms involved in drug abuse and addiction?

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.

Para cá e para lá dos muros: relações familiares na interface entre o interior e o exterior da prisão

Tese de Doutoramento em Sociologia

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

An assessment of chronic kidney diseases

Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

An evaluation of parchments' degradation a hybrid approach

Parchment stands for a multifaceted material made from animal skin, which has been used for centuries as a writing support or as bookbinding. Due to the historic value of objects made of parchment, understanding their degradation and their condition is of utmost importance to archives, libraries and museums, i.e., the assessment of parchment degradation is mandatory, although it is hard to do with traditional methodologies and tools for problem solving. Hence, in this work we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate Parchment Degradation and the respective Degree-of-Confidence that one has on such a happening.

Educação e ambiguidades da autonomização: para uma pedagogia crítica da promoção do indivíduo autónomo

O presente artigo, confrontando a educação com o desiderato da autonomização, pretende analisar as ambiguidades a que esse confronto dá hoje origem e estabelecer, mediante a explicitação de uma conceção contra-hegemónica de autonomização, as bases e as coordenadas de uma pedagogia crítica da promoção do indivíduo autónomo, que seja simultaneamente humanista, emancipadora e transformadora tanto da realidade do sujeito quanto da realidade do contexto. A estrutura narrativa, em consonância com esse amplo propósito, articula as seguintes dimensões: a educação e a normatividade da autonomização; as ambiguidades da autonomização: sentidos divergentes de fazer educação para a autonomia; e, por fim, o empowerment emancipatório e transformador: vetor da educação enquanto autonomização contra-hegemónica. A conclusão aponta as linhas diretoras da construção de uma pedagogia crítica do indivíduo autónomo, assumida nas vertentes de emancipação individual e transformação social.

Orientação para o mercado e desenvolvimento de novos produtos: um estudo de caso

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Micro- and mesoporous structures as drug delivery carriers for salicylic acid

The potential of salicylic acid (SA) encapsulated in porous materials as drug delivery carriers for cancer treatment was studied. Different porous structures, the microporous zeolite NaY, and the mesoporous SBA-15 and MCM-41 were used as hosts for the anti-inflammatory drug. Characterization with different techniques (FTIR, UV/vis, TGA, 1H NMR, and 13C CPMAS NMR) demonstrated the successful loading of SA into the porous hosts. The mesoporous structures showed to be very efficient to encapsulate the SA molecule. The obtained drug delivery systems (DDS) accommodated 0.74 mmol (341 mg/gZEO) in NaY and 1.07 mmol (493 mg/gZEO) to 1.23 mmol (566 mg/gZEO) for SBA-15 and MCM-41, respectively. Interactions between SA molecules and pore structures were identified. A fast and unrestricted liberation of SA at 10 min of the dissolution assay was achieved with 29.3, 46.6, and 50.1 µg/mL of SA from NaY, SBA-15, and MCM-41, respectively, in the in vitro drug release studies (PBS buffer pH 7.4, 37 °C). Kinetic modeling was used to determine the release patterns of the DDS. The porous structures and DDS were evaluated on Hs578T and MDA-MB-468 breast cancer cell lines viability. The porous structures are nontoxic to cancer cells. Cell viability reduction was only observed after the release of SA from MCM- 41 followed by SBA-15 in both breast cancer cell lines.

Searching for therapeutic strategies in a mouse modelo of Machado-Joseph disease: targeting proteostases

Tese de Doutoramento em Ciências da Saúde

Atuação dos enfermeiros na emergência pré-hospitalar em situações de paragem cárdio-respiratória

Dissertação de mestrado em Enfermagem da Pessoa em Situação Crítica

[Comunicação no I Encontro de Jovens Investigadores em Ciências da Comunicação – SOPCOM]

O dia 7 de Janeiro de 2011 é uma data extraordinário para o Centro de Estudos de Comunicação e Sociedade (CECS), por duas razões principais. A primeira é porque a equipa de investigadores deste Centro – seniores e juniores – se sente, desde o seu início, profundamente comprometida com a construção da comunidade académica das Ciências da Comunicação em Portugal, a qual, como sabem, é uma comunidade jovem. A segunda é porque este vosso evento, ao qual gostosamente se associa, acabou por ser o primeiro acto dos dez anos de vida que o CECS assinala em 2011. Este Centro é, pois, ainda, uma criança, ainda que tenha já uma trajectória que fez dele uma unidade de excelência na investigação no nosso país, na nossa disciplina ou interdisciplina. Sendo um grupo jovem, é por natureza especialmente sensível à ousadia que teve o grupo organizador de vos convocar e vos acolher. Estou certo que as energias e as questões novas que o vosso grupo e os vossos debates enunciarão vão trazer uma etapa nova e promissora à SOPCOM, enriquecendo a sua agenda programática e conferindo-lhe uma vitalidade nova.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.