937 resultados para Bromelia antiacantha extract


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The aim of this study was to investigate the molecular basis of human IgE-allergen interaction by screening a phage-displayed peptide library with an allergen-specific human IgE-mimicking monoclonal antibody (mAb). A mAb that reacted with major grass pollen allergens was successfully identified and shown to inhibit human IgE-allergen interaction. Biopanning of a phage-displayed random peptide library with this mAb yielded a 12 amino acid long mimotope. A synthetic peptide based on this 12-mer mimotope inhibited mAb and human IgE binding to grass pollen extracts. Our results indicate that such synthetic peptide mimotopes of allergens have potential as novel therapeutic agents. © 2001 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

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Purified proteins are mandatory for molecular, immunological and cellular studies. However, purification of proteins from complex mixtures requires specialised chromatography methods (i.e., gel filtration, ion exchange, etc.) using fast protein liquid chromatography (FPLC) or high-performance liquid chromatography (HPLC) systems. Such systems are expensive and certain proteins require two or more different steps for sufficient purity and generally result in low recovery. The aim of this study was to develop a rapid, inexpensive and efficient gel-electrophoresis-based protein purification method using basic and readily available laboratory equipment. We have used crude rye grass pollen extract to purify the major allergens Lol p 1 and Lol p 5 as the model protein candidates. Total proteins were resolved on large primary gel and Coomassie Brilliant Blue (CBB)-stained Lol p 1/5 allergens were excised and purified on a secondary "mini"-gel. Purified proteins were extracted from unstained separating gels and subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblot analyses. Silver-stained SDS-PAGE gels resolved pure proteins (i.e., 875 μg of Lol p 1 recovered from a 8 mg crude starting material) while immunoblot analysis confirmed immunological reactivity of the purified proteins. Such a purification method is rapid, inexpensive, and efficient in generating proteins of sufficient purity for use in monoclonal antibody (mAb) production, protein sequencing and general molecular, immunological, and cellular studies.

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Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

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This paper describes ongoing work on a system using spatial descriptions to construct abstract maps that can be used for goal-directed exploration in an unfamiliar office environment. Abstract maps contain membership, connectivity, and spatial layout information extracted from symbolic spatial information. In goal-directed exploration, the robot would then link this information with observed symbolic information and its grounded world representation. We demonstrate the ability of the system to extract and represent membership, connectivity, and spatial layout information from spatial descriptions of an office environment. In the planned study, the robot will navigate to the goal location using the abstract map to inform the best direction to explore in.

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Information available on company websites can help people navigate to the offices of groups and individuals within the company. Automatically retrieving this within-organisation spatial information is a challenging AI problem This paper introduces a novel unsupervised pattern-based method to extract within-organisation spatial information by taking advantage of HTML structure patterns, together with a novel Conditional Random Fields (CRF) based method to identify different categories of within-organisation spatial information. The results show that the proposed method can achieve a high performance in terms of F-Score, indicating that this purely syntactic method based on web search and an analysis of HTML structure is well-suited for retrieving within-organisation spatial information.

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Acoustic classification of anurans (frogs) has received increasing attention for its promising application in biological and environment studies. In this study, a novel feature extraction method for frog call classification is presented based on the analysis of spectrograms. The frog calls are first automatically segmented into syllables. Then, spectral peak tracks are extracted to separate desired signal (frog calls) from background noise. The spectral peak tracks are used to extract various syllable features, including: syllable duration, dominant frequency, oscillation rate, frequency modulation, and energy modulation. Finally, a k-nearest neighbor classifier is used for classifying frog calls based on the results of principal component analysis. The experiment results show that syllable features can achieve an average classification accuracy of 90.5% which outperforms Mel-frequency cepstral coefficients features (79.0%).

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The glass transition, whereby liquids transform into amorphous solids at low temperatures, is a subject of intense research despite decades of investigation. Explaining the enormous increase in relaxation times of a liquid upon supercooling is essential for understanding the glass transition. Although many theories, such as the Adam-Gibbs theory, have sought to relate growing relaxation times to length scales associated with spatial correlations in liquid structure or motion of molecules, the role of length scales in glassy dynamics is not well established. Recent studies of spatially correlated rearrangements of molecules leading to structural relaxation, termed ``spatially heterogeneous dynamics,'' provide fresh impetus in this direction. A powerful approach to extract length scales in critical phenomena is finite-size scaling, wherein a system is studied for sizes traversing the length scales of interest. We perform finite-size scaling for a realistic glass-former, using computer simulations, to evaluate the length scale associated with spatially heterogeneous dynamics, which grows as temperature decreases. However, relaxation times that also grow with decreasing temperature do not exhibit standard finite-size scaling with this length. We show that relaxation times are instead determined, for all studied system sizes and temperatures, by configurational entropy, in accordance with the Adam-Gibbs relation, but in disagreement with theoretical expectations based on spin-glass models that configurational entropy is not relevant at temperatures substantially above the critical temperature of mode-coupling theory. Our results provide new insights into the dynamics of glass-forming liquids and pose serious challenges to existing theoretical descriptions.

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Background Different from other indicators of cardiac function, such as ejection fraction and transmitral early diastolic velocity, myocardial strain is promising to capture subtle alterations that result from early diseases of the myocardium. In order to extract the left ventricle (LV) myocardial strain and strain rate from cardiac cine-MRI, a modified hierarchical transformation model was proposed. Methods A hierarchical transformation model including the global and local LV deformations was employed to analyze the strain and strain rate of the left ventricle by cine-MRI image registration. The endocardial and epicardial contour information was introduced to enhance the registration accuracy by combining the original hierarchical algorithm with an Iterative Closest Points using Invariant Features algorithm. The hierarchical model was validated by a normal volunteer first and then applied to two clinical cases (i.e., the normal volunteer and a diabetic patient) to evaluate their respective function. Results Based on the two clinical cases, by comparing the displacement fields of two selected landmarks in the normal volunteer, the proposed method showed a better performance than the original or unmodified model. Meanwhile, the comparison of the radial strain between the volunteer and patient demonstrated their apparent functional difference. Conclusions The present method could be used to estimate the LV myocardial strain and strain rate during a cardiac cycle and thus to quantify the analysis of the LV motion function.

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The world is rich with information such as signage and maps to assist humans to navigate. We present a method to extract topological spatial information from a generic bitmap floor plan and build a topometric graph that can be used by a mobile robot for tasks such as path planning and guided exploration. The algorithm first detects and extracts text in an image of the floor plan. Using the locations of the extracted text, flood fill is used to find the rooms and hallways. Doors are found by matching SURF features and these form the connections between rooms, which are the edges of the topological graph. Our system is able to automatically detect doors and differentiate between hallways and rooms, which is important for effective navigation. We show that our method can extract a topometric graph from a floor plan and is robust against ambiguous cases most commonly seen in floor plans including elevators and stairwells.

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The appealing concept of optimal harvesting is often used in fisheries to obtain new management strategies. However, optimality depends on the objective function, which often varies, reflecting the interests of different groups of people. The aim of maximum sustainable yield is to extract the greatest amount of food from replenishable resources in a sustainable way. Maximum sustainable yield may not be desirable from an economic point of view. Maximum economic yield that maximizes the profit of fishing fleets (harvesting sector) but ignores socio-economic benefits such as employment and other positive externalities. It may be more appropriate to use the maximum economic yield that which is based on the value chain of the overall fishing sector, to reflect better society's interests. How to make more efficient use of a fishery for society rather than fishing operators depends critically on the gain function parameters including multiplier effects and inclusion or exclusion of certain costs. In particular, the optimal effort level based on the overall value chain moves closer to the optimal effort for the maximum sustainable yield because of the multiplier effect. These issues are illustrated using the Australian Northern Prawn Fishery.

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Oksidatiivisen stressin eli liiallisen reaktiivisten happiyhdisteiden määrän soluissa on jo pitkään arveltu olevan tärkeä Alzheimerin taudin kehittymiseen ja etenemiseen vaikuttava tekijä. Tämän vuoksi kiinnostus erilaisten antioksidanttien (yhdisteitä, jotka neutraloivat näitä happiradikaaleja soluissa) mahdollisia terapeuttisia ominaisuuksia Alzheimerin taudin hoidossa on tutkittu laajalti. Tähän mennessä ei kuitenkaan ole vielä onnistuttu löytämään antioksidanttia, joka olisi hyödyksi Alzheimerin taudin hoidossa. Tämän vuoksi on tärkeää pyrkiä löytämään uusia antioksidanttien lähteitä sekä tutkia niistä löytyviä aktiivisia yhdisteitä. Kiinnostus luonnon antioksidantteja kohtaan on kasvanut voimakkaasti viime aikoina. Huomio on kiinnittynyt erityisesti aromaattisista sekä lääkekasveista löytyviin antioksidantteihin. Lamiaceae- perheeseen kuuluvia tuoksuampiaisyrttiä (Dracocephalum moldavica L.) ja sitruunamelissaa (Melissa officinalis L.) on käytetty Iranissa pitkään sekä ruoanlaitossa että lääkinnässä, minkä vuoksi näiden kasvien uutteiden antioksidanttisisältöä päätettiin analysoida käyttäen useaa erilaista in vitro- menetelmää. Näissä kokeissa ilmeni, että uutteilla oli useita antioksidanttisia vaikutuksia. Näistä antioksidanttisista vaikutuksista vastaavia yhdisteitä pyrittiin tunnistamaan käyttäen HPLC-PDA- tekniikkaa, minkä seurauksena niiden havaittiin sisältävän erilaisia polyfenoleita, kuten hydroksyloituneita bentsoeeni- ja cinnamamidihapon johdannaisia sekä flavonoideja. Kummankin kasvin uutteissa runsaimmin esiintynyt yhdiste oli rosmariinihappo. Sitruunamelissaa (M. officinalis) on käytetty antiikin ajoista alkaen kognitiivisten toimintojen häiriöiden hoidossa. Perustuen tietoon kasvin käytöstä perinteisessä lääkinnässä, sen tehoa Alzheimerin taudin hoidossa on tutkittu viime aikoina kliinisin kokein. Sitruunamelissan todettiinkin olevan hyödyksi lievää ja keskivaikeaa Alzheimeimerin tautia sairastavien potilaiden hoidossa. Väitöskirjan osanan olevasta kooste-artikkelista käy ilmi, että tutkimalla lääkekasvien ominaisuuksia voidaan saada arvokkaita suuntaa-antavia vihjeitä Alzheimerin taudin lääkehoidon kehittämiseen. Tämän perusteella päätettiinkin testatata myös sitruunamelissauutteen kykyä estää asetyylikoliiniesteraasin (AChE) toimintaa, koska tämän entsyymin toiminna estämisen tiedetään olevan hyödyksi Alzheimerin taudin hoidossa. Uute kykeni estämään AChE:n toimintaa, minkä vuoksi uutteen sisältämiä komponentteja päätettiin tutkia terkemmin. Uute jaettiin erilaisiin fraktioihin käyttäen HPLC-menetelmää, minkä jälkeen testattiin jokaisen fraktion kykyä inhiboida AchE. Suurin osa fraktioista kykeni inhiboimaan AChE:n toimintaa selkeästi tehokkaammin, kuin raakauute. Kaikista tehokkainta fraktiota analysoitiin tarkemmin sen aktiivisten yhdisteiden tunnistamiseksi, minkä seurauksena sen sisältämät yhdisteet tunnistettiin cis ja trans-rosmariinihapoiksi. Tässä tutkimuksessa tunnistettujen yhdisteiden hyödyllisyyttä Alzheimerin taudin hoidossa tulisi seuraavaksi tutkia erilaisissa in vivo-malleissa. Lisäksi jäljellä olevien fraktioiden kemiallinen koostumus tulisi selvittää sekä antioksidanttiaktiivisuuden ja AChE:n toiminnan inhiboinnin välistä mahdollista yhteyttä tulisi tutkia tarkemmin. Tämä tutkimus osoittaa tuoksuampiasyrtin (D. moldavica) sekä sitruunamelissan (M. officinalis) sisältävän monenlaisia aktiivisia antioksidantteja. Lisäksi sitruunamelissan sisältämät yhdisteet kykenivät estämään asetyylikoliiniesteraasin (AchE) toimintaa. Nämä tulokset tukevat osaltaan väitöskirjan osana olevan kooste-artikkelin johtopäätöksiä, joiden mukaan etnofarmakologinen kasvitutkimus voi osoittautua erittäin hyödylliseksi kehitettäessä uutta lääkehoitoa Alzheimerin tautiin. Lisäksi tässä väitöskirjassa kuvattu tutkimus osoittaakin, että perinteisesti lääkekasvina käytettyä sitruunamelissaa voidaan mahdollisesti hyödyntää uusien Alzheimerin taudin hoitoon käytettävien lääkkeiden kehityksessä.

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Natural products constitute an important source of new drugs. The bioavailability of the drugs depends on their absorption, distribution, metabolism and elimination. To achieve good bioavailability, the drug must be soluble in water, stable in the gastrointestinal tract and palatable. Binding proteins may improve the solubility of drug compounds, masking unwanted properties, such as bad taste, bitterness or toxicity, transporting or protecting these compounds during processing and storage. The focus of this thesis was to study the interactions, including ligand binding and the effect of pH and temperature, of bovine and reindeer β-lactoglobulin (βLG) with such compounds as retinoids, phenolic compounds as well as with compounds from plant extracts, and to investigate the transport properties of the βLG-ligand complex. To examine the binding interactions of different ligands to βLG, new methods were developed. The fluorescence binding method for the evaluation of ligand binding to βLG was miniaturized from a quartz cell to a 96-well plate. A method of ultrafiltration sampling combined with high-performance liquid chromatography was developed to assess the binding of compounds from extracts. The interactions of phenolic compounds or retinoids and βLG were investigated using the 96-well plate method. The majority of flavones, flavonols, flavanones and isoflavones and all of the retinoids included were shown to bind to bovine and reindeer βLG. Phenolic compounds, contrary to retinol, were not released at acidic pH. Those results suggest that βLG may have more binding sites, probably also on the surface of βLG. An extract from Camellia sinensis (L.) O. Kunze (black tea), Urtica dioica L. (nettle) and Piper nigrum (black pepper) were used to evaluate whether βLG could bind compounds from plant extracts. Piperine from P. nigrum was found to bind tightly and rutin from U. dioica weakly to βLG. No components from C. sinensis bound to βLG in our experiment. The uptake and membrane permeation of bovine and reindeer βLG, free and bound with retinol, palmitic acid and cholesterol, were investigated using Caco-2 cell monolayers. Both bovine and reindeer βLG were able to cross the Caco-2 cell membrane. Free and βLG-bound retinol and palmitic acid were transported equally, whereas cholesterol could not cross the Caco-2 cell monolayer free or bound to βLG. Our results showed that βLG can bind different natural product compounds, but cannot enhance transport of retinol, palmitic acid or cholesterol through Caco-2 cells. Despite this, βLG, as a water-soluble binding protein, may improve the solubility of natural compounds, possibly protecting them from early degradation and transporting some of them through the stomach. Furthermore, it may decrease their bad or bitter taste during oral administration of drugs or in food preparations. βLG can also enhance or decrease the health benefits of herbal teas and food preparations by binding compounds from extracts.

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Colorectal cancer (CRC) is a major health concern and demands long-term efforts in developing strategies for screening and prevention. CRC has become a preventable disease as a consequence of a better understanding of colorectal carcinogenesis. However, current therapy is unsatisfactory and necessitates the exploration of other approaches for the prevention and treatment of cancer. Plant based products have been recognized as preventive with regard to the development of colon cancer. Therefore, the potential chemopreventive use and mechanism of action of Lebanese natural product were evaluated. Towards this aim the antitumor activity of Onopordum cynarocephalum and Centaurea ainetensis has been studied using in vitro and in vivo models. In vitro, both crude extracts were non cytotoxic to normal intestinal cells and inhibited the proliferation of colon cancer cells in a dose-dependent manner. In vivo, both crude extracts reduced the number of tumors by an average of 65% at weeks 20 (adenomas stage) and 30 (adenocarcinomas stage). The activity of the C. ainetensis extract was attributed to Salograviolide A, a guaianolide-type sesquiterpene lactone, which was isolated and identified through bio-guided fractionation. The mechanism of action of thymoquinone (TQ), the active component of Nigella sativa, was established in colon cancer cells using in vitro models. By the use of N-acetyl cysteine, a radical scavenger, the direct involvement of reactive oxygen species in TQ-induced apoptotic cells was established. The analytical detection of TQ from spiked serum and its protein binding were evaluated. The average recovery of TQ from spiked serum subjected to several extraction procedures was 2.5% proving the inability of conventional methods to analyze TQ from serum. This has been explained by the extensive binding (>98%) of TQ to serum and major serum components such as bovine serum albumin (BSA) and alpha-1-acid glycoprotein (AGP). Using mass spectrometry analysis, TQ was confirmed to bind covalently to the free cysteine in position 34 and 147 of the amino acid sequence of BSA and AGP, respectively. The results of this work put at the disposal for future development new plants with anti-cancer activities and enhance the understanding of the pharmaceutical properties of TQ, a prerequisite for its future clinical development.

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- Introduction There is limited understanding of how young adults’ driving behaviour varies according to long-term substance involvement. It is possible that regular users of amphetamine-type stimulants (i.e. ecstasy (MDMA) and methamphetamine) may have a greater predisposition to engage in drink/drug driving compared to non-users. We compare offence rates, and self-reported drink/drug driving rates, for stimulant users and non-users in Queensland, and examine contributing factors. - Methods The Natural History Study of Drug Use is a prospective longitudinal study using population screening to recruit a probabilistic sample of amphetamine-type stimulant users and non-users aged 19-23 years. At the 4 ½ year follow-up, consent was obtained to extract data from participants’ Queensland driver records (ATS users: n=217, non-users: n=135). Prediction models were developed of offence rates in stimulant users controlling for factors such as aggression and delinquency. - Results Stimulant users were more likely than non-users to have had a drink-driving offence (8.7% vs. 0.8%, p < 0.001). Further, about 26% of ATS users and 14% of non-users self-reported driving under the influence of alcohol during the last 12 months. Among stimulant users, drink-driving was independently associated with last month high-volume alcohol consumption (Incident Rate Ratio (IRR): 5.70, 95% CI: 2.24-14.52), depression (IRR: 1.28, 95% CI: 1.07-1.52), low income (IRR: 3.57, 95% CI: 1.12-11.38), and male gender (IRR: 5.40, 95% CI: 2.05-14.21). - Conclusions Amphetamine-type stimulant use is associated with increased long-term risk of drink-driving, due to a number of behavioural and social factors. Inter-sectoral approaches which target long-term behaviours may reduce offending rates.

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Australia’s rangelands are the extensive arid and semi-arid grazing lands that cover approximately 70% of the Australian continent. They are characterised by low and generally variable rainfall, low productivity and a sparse population. They support a number of industries including mining and tourism, but pastoralism is the primary land use. In some areas, the rangelands have a history of biological decline (Noble 1997), with erosion, loss of perennial native grasses and incursion of woody vegetation commonly reported in the scientific and lay literature. Despite our historic awareness of these trends, the establishment of systems to measure and monitor degradation, has presented numerous problems. The size and accessibility of Australia’s rangeland often mitigates development of extensive monitoring programs. So, too, securing on-going commitment from Government agencies to fund rangeland monitoring activities have led to either abandonment or a scaled-down approach in some instances (Graetz et al. 1986; Holm 1993). While a multiplicity of monitoring schemes have been developed for landholders at the property scale, and some have received promising initial uptake, relatively few have been maintained for more than a few years on any property without at least some agency support (Pickup et al. 1998). But, ironically, such property level monitoring tools can contribute significantly to local decisions about stock, infrastructure and sustainability. Research in recent decades has shown the value of satellites for monitoring change in rangelands (Wallace et al. 2004), especially in terms of tree and ground cover. While steadily improving, use of satellite data as a monitoring tool has been limited by the cost of the imagery, and the equipment and expertise needed to extract useful information from it. A project now under way in the northern rangelands of Australia is attempting to circumvent many of the problems through a monitoring system that allows property managers to use long-term satellite image sequences to quickly and inexpensively track changes in land cover on their properties