979 resultados para medicinal mushroom


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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.

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A new family of neural network architectures is presented. This family of architectures solves the problem of constructing and training minimal neural network classification expert systems by using switching theory. The primary insight that leads to the use of switching theory is that the problem of minimizing the number of rules and the number of IF statements (antecedents) per rule in a neural network expert system can be recast into the problem of minimizing the number of digital gates and the number of connections between digital gates in a Very Large Scale Integrated (VLSI) circuit. The rules that the neural network generates to perform a task are readily extractable from the network's weights and topology. Analysis and simulations on the Mushroom database illustrate the system's performance.

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This work examines the origins and early history of the Queen's College, Cork. Designedly there is as much stress on the origins as on the early history, for it is the contention of the work that the College was something more than a legislative mushroom. It was very much in the tradition of the civic universities which added an exciting new dimension to academic life in these islands in the nineteenth century. The first chapter surveys university practice and thinking at the opening of the century, relying exclusively on published sources. The second chapter is devoted specifically to the state of learning in Cork during the period, and makes extensive use of hitherto unpublished manuscript material in relation to the Royal Cork Institution. The third chapter deals with the highly significant evidence on education embodied in the Report of the Select Committee on Irish Education of 1838. This material has not previously been published. In chapter four an extended study is made of relevant letters in the manuscript correspondence of Sir Robert Peel - even the most recent authoritative biography has ignored this material. The remaining three chapters are devoted more specifically to the College, both in the formulation or policy and in its practical working. In chapter six there is an extended survey of early College life based exclusively on hitherto unpublished manuscript material in the College Archives. All of these sources, together with incidental published material, are set out at the end of each chapter.

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This thesis investigates the extent and range of the ocular vocabulary and themes employed by the playwright Thomas Middleton in context with early modern scientific, medical, and moral-philosophical writing on vision. More specifically, this thesis concerns Middleton’s revelation of the substance or essence of outward forms through mimesis. This paradoxical stance implies Middleton’s use of an illusory (theatrical) art form to explore hidden truths. This can be related to the early modern belief in the imagination (or fantasy) as chief mediator between the corporeal and spiritual worlds as well as to a reformed belief in the power of signs to indicate divine truth. This thesis identifies striking parallels between Middleton’s policy of social diagnosis and cure and an increased preoccupation with knowledge of interior man which culminates in Robert Burton’s Anatomy of Melancholy of 1621. All of these texts seek a cure for diseased internal sense faculties (such as fantasy and will) which cause the raging passions to destroy the individual. The purpose of this thesis is to demonstrate how Middleton takes a similar ‘mental-medicinal’ approach which investigates the idols created by the imagination before ‘purging’ the same and restoring order (Corneanu and Vermeir 184). The idea of infection incurred through the eyes which are fixed on vice (or error) has moral, religious, and political implications and discovery of corruption involves stripping away the illusions of false appearances to reveal the truth within whereby disease and disorder can be cured and restored. Finally, Middleton’s use of theatrical fantasy to detect the idols of the diseased imagination can be read as a Paracelsian, rather than Galenic, form of medicine whereby like is ‘joined with their like’ (Bostocke C7r) to restore health.

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Recent studies have shown that deoxygenated human red blood cells (RBCs) converted garlic-derived polysulfides into hydrogen sulfide, which in turn produced vasorelaxation in aortic ring preparations. The vasoactivity was proposed to occur via glucose- and thiol-dependent acellular reactions. In the present study, we investigated the interaction of garlic extracts with human deoxygenated RBCs and its effect on intracellular hemoglobin molecules. The results showed that garlic extract covalently modified intraerythrocytic deoxygenated hemoglobin. The modification identified consisted of an addition of 71 atomic mass units, suggesting allylation of the cysteine residues. Consistently, purified human deoxyhemoglobin reacted with chemically pure diallyl disulfide, showing the same modification as garlic extracts. Tandem mass spectrometry analysis demonstrated that garlic extract and diallyl disulfide modified hemoglobin's beta-chain at cysteine-93 (beta-93C) or cysteine-112 (beta-112C). These results indicate that garlic-derived organic disulfides as well as pure diallyl disulfide must permeate the RBC membrane and modified deoxyhemoglobin at beta-93C or beta-112C. Although the physiological role of the reported garlic extract-induced allyl modification on human hemoglobin warrants further study, the results indicate that constituents of natural products, such as those from garlic extract, modify intracellular proteins.

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In our continuing study of triterpene derivatives as potent anti-HIV agents, different C-3 conformationally restricted betulinic acid (BA, 1) derivatives were designed and synthesized in order to explore the conformational space of the C-3 pharmacophore. 3-O-Monomethylsuccinyl-betulinic acid (MSB) analogues were also designed to better understand the contribution of the C-3' dimethyl group of bevirimat (2), the first-in-class HIV maturation inhibitor, which is currently in phase IIb clinical trials. In addition, another triterpene skeleton, moronic acid (MA, 3), was also employed to study the influence of the backbone and the C-3 modification toward the anti-HIV activity of this compound class. This study enabled us to better understand the structure-activity relationships (SAR) of triterpene-derived anti-HIV agents and led to the design and synthesis of compound 12 (EC(50): 0.0006 microM), which displayed slightly better activity than 2 as a HIV-1 maturation inhibitor.

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Gemstone Team ANTIDOTE

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All biological phenomena depend on molecular recognition, which is either intermolecular like in ligand binding to a macromolecule or intramolecular like in protein folding. As a result, understanding the relationship between the structure of proteins and the energetics of their stability and binding with others (bio)molecules is a very interesting point in biochemistry and biotechnology. It is essential to the engineering of stable proteins and to the structure-based design of pharmaceutical ligands. The parameter generally used to characterize the stability of a system (the folded and unfolded state of the protein for example) is the equilibrium constant (K) or the free energy (deltaG(o)), which is the sum of enthalpic (deltaH(o)) and entropic (deltaS(o)) terms. These parameters are temperature dependent through the heat capacity change (deltaCp). The thermodynamic parameters deltaH(o) and deltaCp can be derived from spectroscopic experiments, using the van't Hoff method, or measured directly using calorimetry. Along with isothermal titration calorimetry (ITC), differential scanning calorimetry (DSC) is a powerful method, less described than ITC, for measuring directly the thermodynamic parameters which characterize biomolecules. In this article, we summarize the principal thermodynamics parameters, describe the DSC approach and review some systems to which it has been applied. DSC is much used for the study of the stability and the folding of biomolecules, but it can also be applied in order to understand biomolecular interactions and can thus be an interesting technique in the process of drug design.