979 resultados para microRNA Target Prediction
Resumo:
Modeling methods to derive 3D-structure of proteins have been recently developed. Protein homology-modeling, also known as comparative protein modeling, is nowadays the most accurate protein modeling method. This technique can produce useful models for about an order of magnitude more protein sequences than there have been structures determined by experiment in the same amount of time. All current protein homology-modeling methods consist of four sequential steps: fold assignment and template selection, template-target alignment, model building, and model evaluation. In this paper we discuss in some detail the protein-homology paradigm, its predictive power and its limitations.
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BACKGROUND: Aging is characterized by a low-grade systemic inflammation that contributes to the pathogenesis of neurodegenerative disorders such as Alzheimer's disease (AD). However, little knowledge is currently available on the molecular processes leading to chronic neuroinflammation. In this context, recent studies have described the role of chromatin regulators in inflammation and longevity including the REST corepressor (Rcor)-2 factor, which seems to be involved in an inflammatory suppressive program. METHODS: To assess the impact of Rcor2 in age-related inflammation, gene expression levels were quantified in different tissues and ages of the spontaneous senescence-accelerated P8 mouse (P8) using the SAMR1 mouse (R1) as a control. Specific siRNA transfection in P8 and R1 astrocyte cultures was used to determine Rcor2 involvement in the modulation of neuroinflammation. The effect of lipopolysaccharide (LPS) treatment on Rcor2 levels and neuroinflammation was analyzed both in vivo and in vitro. RESULTS: P8 mice presented a dramatic decrease in Rcor2 gene expression compared with R1 controls in splenocytes, an alteration also observed in the brain cortex, hippocampus and primary astrocytes of these mice. Rcor2 reduction in astrocytes was accompanied by an increased basal expression of the interleukin (Il)-6 gene. Strikingly, intraperitoneal LPS injection in R1 mice downregulated Rcor2 in the hippocampus, with a concomitant upregulation of tumor necrosis factor (Tnf-α), Il1-β and Il6 genes. A negative correlation between Rcor2 and Il6 gene expression was also verified in LPS-treated C6 glioma cells. Knock down of Rcor2 by siRNA transfection (siRcor2) in R1 astrocytes upregulated Il6 gene expression while siRcor2 further increased Il6 expression in P8 astrocytes. Moreover, LPS activation provoked a further downregulation of Rcor2 and an amplified induction of Il6 in siRcor2-tranfected astrocytes. CONCLUSIONS: Data presented here show interplay between Rcor2 downregulation and increased inflammation and suggest that Rcor2 may be a key regulator of inflammaging
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Automobile bodily injury (BI) claims remain unsettled for a long time after the accident. The estimation of an accurate reserve for Reported But Not Settled (RBNS) claims is therefore vital for insurers. In accordance with the recommendation included in the Solvency II project (CEIOPS, 2007) a statistical model is here implemented for RBNS reserve estimation. Lognormality on empirical compensation cost data is observed for different levels of BI severity. The individual claim provision is estimated by allocating the expected mean compensation for the predicted severity of the victim’s injury, for which the upper bound is also computed. The BI severity is predicted by means of a heteroscedastic multiple choice model, because empirical evidence has found that the variability in the latent severity of injured individuals travelling by car is not constant. It is shown that this methodology can improve the accuracy of RBNS reserve estimation at all stages, as compared to the subjective assessment that has traditionally been made by practitioners.
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Diplomityön tavoitteena on selvittää Loviisan ydinvoimalaitoksen höyryturbiinin hyötysuhteen parantamismahdollisuuksia. Työn kuvaan liittyvät oleellisesti höyryturbiinin siipivyöhykkeiden nopeuskolmioiden sekä hyötysuhteiden laskenta. Höyryturbiinien kehityskaarta sekä turbiinin häviökerrointen laskentayhtälöitä on esitetty useasta eri lähteestä ja vuosikymmeniltä. Työssä selvitettiin uusimpia ydinvoimalaitosten kostea höyryturbiinien suunnitteluperusteita lukuisista eri lähteistä. Kaikkien lähteiden mukaan kostean höyryn alueella tapahtuvaa paisuntaa on haasteellista mallintaa. Työssä on esitelty artikkeleissa tulleita eri näkökulmia höyryturbiinien suorituskyvyn parantamiseksi, sekä rakenteellisia että laskennallisia. Työssä esitellään monia turbiinin virtauksen ja suorituskyvyn laskentamenetelmiä. Esimerkiksi Baumannin säännön laskenta on yksinkertainen tapa käsitellä turbiinin suorituskykyä kostean höyryn alueella. Keskeisimpiä tehtyjä havaintoja oli se, että korkeapaineturbiinin ensimmäisestä vaiheesta löytyi mahdollista parannuspotentiaalia Loviisaan ydinvoimalaitoksen tehon lisäämiseksi. Ensimmäisessä vaiheessa on oletettu siipien olevan Laval –tyyppisiä, mutta käytännössä näin ei ole. Korkeapaineturbiinin nykyisen turbosuuttimen toimintaa voitaisiin tehostaa. Lisäksi Loviisan matalapaineturbiinin viimeisen siipivaiheen jälkeen aiheutuu suuret ulosvirtaushäviöt. Osa suurinopeuksisen virtauksen energiasta pystyttäisiin kuitenkin hyödyntämään vielä ulosvirtauskanavassa olevalla diffuusorilla.
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We have synthesized a family of rhein-huprine hybrids to hit several key targets for Alzheimer"s disease. Biological screening performed in vitro and in Escherichia coli cells has shown that these hybrids exhibit potent inhibitory activities against human acetylcholinesterase butyrylcholinesterase, and BACE-1, dual Aβ42 and tau anti-aggregating activity, and brain permeability. Ex vivo studies with the leads (+)- and (-)-7e in brain slices of C57bl6 mice have revealed that they efficiently protect against the Aβ-induced synaptic dysfunction , preventing the loss of synaptic proteins and/or have a positive effect on the induction of long term potentiation. In vivo studies in APP-PS1 transgenic mice treated i.p. for 4 weeks with (+)- and (-)-7e have shown a central soluble Aβ lowering effect, accompanied by an increase in the levels of mature amyloid precursor protein (APP). Thus, (+)- and (-)-7e emerge as very promising disease-modifying anti-Alzheimer drug candidates.
Resumo:
We have synthesized a family of rhein-huprine hybrids to hit several key targets for Alzheimer"s disease. Biological screening performed in vitro and in Escherichia coli cells has shown that these hybrids exhibit potent inhibitory activities against human acetylcholinesterase butyrylcholinesterase, and BACE-1, dual Aβ42 and tau anti-aggregating activity, and brain permeability. Ex vivo studies with the leads (+)- and (-)-7e in brain slices of C57bl6 mice have revealed that they efficiently protect against the Aβ-induced synaptic dysfunction , preventing the loss of synaptic proteins and/or have a positive effect on the induction of long term potentiation. In vivo studies in APP-PS1 transgenic mice treated i.p. for 4 weeks with (+)- and (-)-7e have shown a central soluble Aβ lowering effect, accompanied by an increase in the levels of mature amyloid precursor protein (APP). Thus, (+)- and (-)-7e emerge as very promising disease-modifying anti-Alzheimer drug candidates.
Resumo:
Notwithstanding the functional role that the aggregates of some amyloidogenic proteins can play in different organisms, protein aggregation plays a pivotal role in the pathogenesis of a large number of human diseases. One of such diseases is Alzheimer"s disease (AD), where the overproduction and aggregation of the β-amyloid peptide (Aβ) are regarded as early critical factors. Another protein that seems to occupy a prominent position within the complex pathological network of AD is the enzyme acetylcholinesterase (AChE), with classical and non-classical activities involved at the late (cholinergic deficit) and early (Aβ aggregation) phases of the disease. Dual inhibitors of Aβ aggregation and AChE are thus emerging as promising multi-target agents with potential to efficiently modify the natural course of AD. In the initial phases of the drug discovery process of such compounds, in vitro evaluation of the inhibition of Aβ aggregation is rather troublesome, as it is very sensitive to experimental assay conditions, and requires expensive synthetic Aβ peptides, which makes cost-prohibitive the screening of large compound libraries. Herein, we review recently developed multi-target anti-Alzheimer compounds that exhibit both Aβ aggregation and AChE inhibitory activities, and, in some cases also additional valuable activities such as BACE-1 inhibition or antioxidant properties. We also discuss the development of simplified in vivo methods for the rapid, simple, reliable, unexpensive, and high-throughput amenable screening of Aβ aggregation inhibitors that rely on the overexpression of Aβ42 alone or fused with reporter proteins in Escherichia coli.
Resumo:
We have synthesized a family of rhein-huprine hybrids to hit several key targets for Alzheimer"s disease. Biological screening performed in vitro and in Escherichia coli cells has shown that these hybrids exhibit potent inhibitory activities against human acetylcholinesterase butyrylcholinesterase, and BACE-1, dual Aβ42 and tau anti-aggregating activity, and brain permeability. Ex vivo studies with the leads (+)- and (-)-7e in brain slices of C57bl6 mice have revealed that they efficiently protect against the Aβ-induced synaptic dysfunction , preventing the loss of synaptic proteins and/or have a positive effect on the induction of long term potentiation. In vivo studies in APP-PS1 transgenic mice treated i.p. for 4 weeks with (+)- and (-)-7e have shown a central soluble Aβ lowering effect, accompanied by an increase in the levels of mature amyloid precursor protein (APP). Thus, (+)- and (-)-7e emerge as very promising disease-modifying anti-Alzheimer drug candidates.
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The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.
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Atherosclerosis is a vascular inflammatory disease causing coronary artery disease, myocardial infarct and stroke, the leading causes of death in Finland and in many other countries. The development of atherosclerotic plaques starts already in childhood and is an ongoing process throughout life. Rupture of a plaque and the following occlusion of the vessel is the main reason for myocardial infarct and stroke, but despite extensive research, the prediction of rupture remains a major clinical problem. Inflammation is considered a key factor in the vulnerability of plaques to rupture. Measuring the inflammation in plaques non-invasively is one potential approach for identification of vulnerable plaques. The aim of this study was to evaluate tracers for positron emission tomography (PET) imaging of vascular inflammation. The studies were performed with a mouse model of atherosclerosis by using ex vivo biodistribution, autoradiography and in vivo PET and computed tomography (CT). Several tracers for inflammation activity were tested and compared with the morphology of the plaques. Inflammation in the atherosclerotic plaques was evaluated as expression of active macrophages. Systematic analysis revealed that the uptake of 18F-FDG and 11C-choline, tracers for metabolic activity in inflammatory cells, was more prominent in the atherosclerotic plaques than in the surrounding healthy vessel wall. The tracer for αvβ3 integrin, 18Fgalacto- RGD, was also found to have high potential for imaging inflammation in the plaques. While 11C-PK11195, a tracer targeted to receptors in active macrophages, was shown to accumulate in active plaques, the target-to-background ratio was not found to be ideal for in vivo imaging purposes. In conclusion, tracers for the imaging of inflammation in atherosclerotic plaques can be tested in experimental pre-clinical settings to select potential imaging agents for further clinical testing. 18F-FDG, 18F-galacto-RGD and 11C-choline choline have good properties, and further studies to clarify their applicability for atherosclerosis imaging in humans are warranted.
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Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV) (Q²) between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR) studies.
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The dissertation is based on four articles dealing with recalcitrant lignin water purification. Lignin, a complicated substance and recalcitrant to most treatment technologies, inhibits seriously pulp and paper industry waste management. Therefore, lignin is studied, using WO as a process method for its degradation. A special attention is paid to the improvement in biodegradability and the reduction of lignin content, since they have special importance for any following biological treatment. In most cases wet oxidation is not used as a complete ' mineralization method but as a pre treatment in order to eliminate toxic components and to reduce the high level of organics produced. The combination of wet oxidation with a biological treatment can be a good option due to its effectiveness and its relatively low technology cost. The literature part gives an overview of Advanced Oxidation Processes (AOPs). A hot oxidation process, wet oxidation (WO), is investigated in detail and is the AOP process used in the research. The background and main principles of wet oxidation, its industrial applications, the combination of wet oxidation with other water treatment technologies, principal reactions in WO, and key aspects of modelling and reaction kinetics are presented. There is also given a wood composition and lignin characterization (chemical composition, structure and origin), lignin containing waters, lignin degradation and reuse possibilities, and purification practices for lignin containing waters. The aim of the research was to investigate the effect of the operating conditions of WO, such as temperature, partial pressure of oxygen, pH and initial concentration of wastewater, on the efficiency, and to enhance the process and estimate optimal conditions for WO of recalcitrant lignin waters. Two different waters are studied (a lignin water model solution and debarking water from paper industry) to give as appropriate conditions as possible. Due to the great importance of re using and minimizing the residues of industries, further research is carried out using residual ash of an Estonian power plant as a catalyst in wet oxidation of lignin-containing water. Developing a kinetic model that includes in the prediction such parameters as TOC gives the opportunity to estimate the amount of emerging inorganic substances (degradation rate of waste) and not only the decrease of COD and BOD. The degradation target compound, lignin is included into the model through its COD value (CODligning). Such a kinetic model can be valuable in developing WO treatment processes for lignin containing waters, or other wastewaters containing one or more target compounds. In the first article, wet oxidation of "pure" lignin water was investigated as a model case with the aim of degrading lignin and enhancing water biodegradability. The experiments were performed at various temperatures (110 -190°C), partial oxygen pressures (0.5 -1.5 MPa) and pH (5, 9 and 12). The experiments showed that increasing the temperature notably improved the processes efficiency. 75% lignin reduction was detected at the lowest temperature tested and lignin removal improved to 100% at 190°C. The effect of temperature on the COD removal rate was lower, but clearly detectable. 53% of organics were oxidized at 190°C. The effect of pH occurred mostly on lignin removal. Increasing the pH enhanced the lignin removal efficiency from 60% to nearly 100%. A good biodegradability ratio (over 0.5) was generally achieved. The aim of the second article was to develop a mathematical model for "pure" lignin wet oxidation using lumped characteristics of water (COD, BOD, TOC) and lignin concentration. The model agreed well with the experimental data (R2 = 0.93 at pH 5 and 12) and concentration changes during wet oxidation followed adequately the experimental results. The model also showed correctly the trend of biodegradability (BOD/COD) changes. In the third article, the purpose of the research was to estimate optimal conditions for wet oxidation (WO) of debarking water from the paper industry. The WO experiments were' performed at various temperatures, partial oxygen pressures and pH. The experiments showed that lignin degradation and organics removal are affected remarkably by temperature and pH. 78-97% lignin reduction was detected at different WO conditions. Initial pH 12 caused faster removal of tannins/lignin content; but initial pH 5 was more effective for removal of total organics, represented by COD and TOC. Most of the decrease in organic substances concentrations occurred in the first 60 minutes. The aim of the fourth article was to compare the behaviour of two reaction kinetic models, based on experiments of wet oxidation of industrial debarking water under different conditions. The simpler model took into account only the changes in COD, BOD and TOC; the advanced model was similar to the model used in the second article. Comparing the results of the models, the second model was found to be more suitable for describing the kinetics of wet oxidation of debarking water. The significance of the reactions involved was compared on the basis of the model: for instance, lignin degraded first to other chemically oxidizable compounds rather than directly to biodegradable products. Catalytic wet oxidation of lignin containing waters is briefly presented at the end of the dissertation. Two completely different catalysts were used: a commercial Pt catalyst and waste power plant ash. CWO showed good performance using 1 g/L of residual ash gave lignin removal of 86% and COD removal of 39% at 150°C (a lower temperature and pressure than with WO). It was noted that the ash catalyst caused a remarkable removal rate for lignin degradation already during the pre heating for `zero' time, 58% of lignin was degraded. In general, wet oxidation is not recommended for use as a complete mineralization method, but as a pre treatment phase to eliminate toxic or difficultly biodegradable components and to reduce the high level of organics. Biological treatment is an appropriate post treatment method since easily biodegradable organic matter remains after the WO process. The combination of wet oxidation with subsequent biological treatment can be an effective option for the treatment of lignin containing waters.
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Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.