28 resultados para classifier combination
Resumo:
The mechanism behind the immunostimulatory effect of the cationic liposomal vaccine adjuvant dimethyldioctadecylammonium and trehalose 6,6′- dibehenate (DDA:TDB) has been linked to the ability of these cationic vesicles to promote a depot after administration, with the liposomal adjuvant and the antigen both being retained at the injection site. This can be attributed to their cationic nature, since reduction in vesicle size does not influence their distribution profile yet neutral or anionic liposomes have more rapid clearance rates. Therefore the aim of this study was to investigate the impact of a combination of reduced vesicle size and surface pegylation on the biodistribution and adjuvanticity of the formulations, in a bid to further manipulate the pharmacokinetic profiles of these adjuvants. From the biodistribution studies, it was found that with small unilamellar vesicles (SUVs), 10% PEGylation of the formulation could influence liposome retention at the injection site after 4 days, whilst higher levels (25 mol%) of PEG blocked the formation of a depot and promote clearance to the draining lymph nodes. Interestingly, whilst the use of 10% PEG in the small unilamellar vesicles did not block the formation of a depot at the site of injection, it did result in earlier antibody response rates and switch the type of T cell responses from a Th1 to a Th2 bias suggesting that the presence of PEG in the formulation not only control the biodistribution of the vaccine, but also results in different types of interactions with innate immune cells. © 2012 Elsevier B.V.
Resumo:
Lyophilised orally disintegrating tablets (ODTs) have achieved a great success in overcoming dysphagia associated with conventional solid dosage forms. However, the extensive use of saccharides within the formulation limits their use in treatment of chronic illnesses. The current study demonstrates the feasibility of using combination of proline and serine to formulate zero sacharide ODTs and investigates the effect of freezing protocol on sublimation rate and tablets characteristics. The results showed that inclusion of proline and serine improved ODT properties when compared to individual counterparts. Additionally, annealing the ODTs facilitated the sublimation process and shortened the disintegration time. © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
Resumo:
This paper presents a model for measuring personal knowledge development in online learning environments. It is based on Nonaka‘s SECI model of organisational knowledge creation. It is argued that Socialisation is not a relevant mode in the context of online learning and was therefore not covered in the measurement instrument. Therefore, the remaining three of SECI‘s knowledge conversion modes, namely Externalisation, Combination, and Internalisation were used and a measurement instrument was created which also examines the interrelationships between the three modes. Data was collected using an online survey, in which online learners report on their experiences of personal knowledge development in online learning environments. In other words, the instrument measures the magnitude of online learners‘ Externalisation and combination activities as well as their level of internalisation, which is the outcome of their personal knowledge development in online learning.
Resumo:
Cleavage by the proteasome is responsible for generating the C terminus of T-cell epitopes. Modeling the process of proteasome cleavage as part of a multi-step algorithm for T-cell epitope prediction will reduce the number of non-binders and increase the overall accuracy of the predictive algorithm. Quantitative matrix-based models for prediction of the proteasome cleavage sites in a protein were developed using a training set of 489 naturally processed T-cell epitopes (nonamer peptides) associated with HLA-A and HLA-B molecules. The models were validated using an external test set of 227 T-cell epitopes. The performance of the models was good, identifying 76% of the C-termini correctly. The best model of proteasome cleavage was incorporated as the first step in a three-step algorithm for T-cell epitope prediction, where subsequent steps predicted TAP affinity and MHC binding using previously derived models.
Resumo:
Eight otherwise healthy diabetic volunteers took a daily antioxidant supplement consisting of vitamin E (200 IU), vitamin C (250 mg) and α-lipoic acid (90 mg) for a period of 6 weeks. Diabetic dapsone hydroxylamine-mediated methaemoglobin formation and resistance to erythrocytic thiol depletion was compared with age and sex-matched non-diabetic subjects. At time zero, methaemoglobin formation in the non-diabetic subjects was greater at all four time points compared with that of the diabetic subjects. Resistance to glutathione depletion was initially greater in non-diabetic compared with diabetic samples. Half-way through the study (3 weeks), there were no differences between the two groups in methaemoglobin formation and thiol depletion in the diabetic samples was now lower than the non-diabetic samples at 10 and 20 min. At 6 weeks, diabetic erythrocytic thiol levels remained greater than those of non-diabetics. HbA1c values were significantly reduced in the diabetic subjects at 6 weeks compared with time zero values. At 10 weeks, 4 weeks after the end of supplementation, the diabetic HbA1c values significantly increased to the point where they were not significantly different from the time zero values. Total antioxidant status measurement (TAS) indicated that diabetic plasma antioxidant capacity was significantly improved during antioxidant supplementation. Conversion of α-lipoic acid to dihydrolipoic acid (DHLA) in vivo led to potent interference in a standard fructosamine assay kit, negating its use in this study. This report suggests that triple antioxidant therapy in diabetic volunteers attenuates the in vitro experimental oxidative stress of methaemoglobin formation and reduces haemoglobin glycation in vivo. © 2003 Elsevier Science B.V. All rights reserved.
An improved conflicting evidence combination approach based on a new supporting probability distance
Resumo:
To avoid counter-intuitive result of classical Dempster's combination rule when dealing with highly conflict information, many improved combination methods have been developed through modifying the basic probability assignments (BPAs) of bodies of evidence (BOEs) by using a certain measure of the degree of conflict or uncertain information, such as Jousselme's distance, the pignistic probability distance and the ambiguity measure. However, if BOEs contain some non-singleton elements and the differences among their BPAs are larger than 0.5, the current conflict measure methods have limitations in describing the interrelationship among the conflict BOEs and may even lead to wrong combination results. In order to solve this problem, a new distance function, which is called supporting probability distance, is proposed to characterize the differences among BOEs. With the new distance, the information of how much a focal element is supported by the other focal elements in BOEs can be given. Also, a new combination rule based on the supporting probability distance is proposed for the combination of the conflicting evidences. The credibility and the discounting factor of each BOE are generated by the supporting probability distance and the weighted BOEs are combined directly using Dempster's rules. Analytical results of numerical examples show that the new distance has a better capability of describing the interrelationships among BOEs, especially for the highly conflicting BOEs containing non-singleton elements and the proposed new combination method has better applicability and effectiveness compared with the existing methods.
Resumo:
Binocular combination for first-order (luminancedefined) stimuli has been widely studied, but we know rather little about this binocular process for spatial modulations of contrast (second-order stimuli). We used phase-matching and amplitude-matching tasks to assess binocular combination of second-order phase and modulation depth simultaneously. With fixed modulation in one eye, we found that binocularly perceived phase was shifted, and perceived amplitude increased almost linearly as modulation depth in the other eye increased. At larger disparities, the phase shift was larger and the amplitude change was smaller. The degree of interocular correlation of the carriers had no influence. These results can be explained by an initial extraction of the contrast envelopes before binocular combination (consistent with the lack of dependence on carrier correlation) followed by a weighted linear summation of second-order modulations in which the weights (gains) for each eye are driven by the first-order carrier contrasts as previously found for first-order binocular combination. Perceived modulation depth fell markedly with increasing phase disparity unlike previous findings that perceived first-order contrast was almost independent of phase disparity. We present a simple revision to a widely used interocular gain-control theory that unifies first- and second-order binocular summation with a single principle-contrast-weighted summation-and we further elaborate the model for first-order combination. Conclusion: Second-order combination is controlled by first-order contrast.
Resumo:
Topic classification (TC) of short text messages offers an effective and fast way to reveal events happening around the world ranging from those related to Disaster (e.g. Sandy hurricane) to those related to Violence (e.g. Egypt revolution). Previous approaches to TC have mostly focused on exploiting individual knowledge sources (KS) (e.g. DBpedia or Freebase) without considering the graph structures that surround concepts present in KSs when detecting the topics of Tweets. In this paper we introduce a novel approach for harnessing such graph structures from multiple linked KSs, by: (i) building a conceptual representation of the KSs, (ii) leveraging contextual information about concepts by exploiting semantic concept graphs, and (iii) providing a principled way for the combination of KSs. Experiments evaluating our TC classifier in the context of Violence detection (VD) and Emergency Responses (ER) show promising results that significantly outperform various baseline models including an approach using a single KS without linked data and an approach using only Tweets. Copyright 2013 ACM.
Resumo:
Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community.
Resumo:
Energy crops production is considered as environmentally benign and socially acceptable, offering ecological benefits over fossil fuels through their contribution to the reduction of greenhouse gases and acidifying emissions. Energy crops are subjected to persistent policy support by the EU, despite their limited or even marginally negative impact on the greenhouse effect. The present study endeavors to optimize the agricultural income generated by energy crops in a remote and disadvantageous region, with the assistance of linear programming. The optimization concerns the income created from soybean, sunflower (proxy for energy crop), and corn. Different policy scenarios imposed restrictions on the value of the subsidies as a proxy for EU policy tools, the value of inputs (costs of capital and labor) and different irrigation conditions. The results indicate that the area and the imports per energy crop remain unchanged, independently of the policy scenario enacted. Furthermore, corn cultivation contributes the most to iFncome maximization, whereas the implemented CAP policy plays an incremental role in uptaking an energy crop. A key implication is that alternative forms of motivation should be provided to the farmers beyond the financial ones in order the extensive use of energy crops to be achieved.
Resumo:
A new approach is described herein, where neutron reflectivity measurements that probe changes in the density profile of thin films as they absorb material from the gas phase have been combined with a Love wave based gravimetric assay that measures the mass of absorbed material. This combination of techniques not only determines the spatial distribution of absorbed molecules, but also reveals the amount of void space within the thin film (a quantity that can be difficult to assess using neutron reflectivity measurements alone). The uptake of organic solvent vapours into spun cast films of polystyrene has been used as a model system with a view to this method having the potential for extension to the study of other systems. These could include, for example, humidity sensors, hydrogel swelling, biomolecule adsorption or transformations of electroactive and chemically reactive thin films. This is the first ever demonstration of combined neutron reflectivity and Love wave-based gravimetry and the experimental caveats, limitations and scope of the method are explored and discussed in detail.
Resumo:
The airways of most people with cystic fibrosis are colonized with biofilms of the Gram-negative, opportunistic pathogen Pseudomonas aeruginosa. Delivery of antibiotics directly to the lung in the form of dry powder aerosols offers the potential to achieve high local concentrations directly to the biofilms. Unfortunately, current aerosolised antibiotic regimes are unable to efficiently eradicate these biofilms from the airways. We investigated the ability of the innate antimicrobial, lactoferrin, to enhance the activity of two aminoglycoside antibiotics (tobramycin and gentamicin) against biofilms of P. aeruginosa strain PAO1. Biofilms were prepared in 96 well polystyrene plates. Combinations of the antibiotics and various lactoferrin preparations were spray dried. The bacterial cell viability of the various spray dried combinations was determined. Iron-free lactoferrin (apo lactoferrin) induced a 3-log reduction in the killing of planktonic cell by the aminoglycoside antibiotics (p < 0.01) and also reduced both the formation and persistence of P. aeruginosa biofilms (p < 0.01). Combinations of lactoferrin and an aminoglycoside displays potential as an effective new therapeutic strategy in the treatment of P. aeruginosa biofilms infections such as those typical of the CF lungs.