987 resultados para Tri-enzyme Extraction
Resumo:
There is provided a process for the extn. of at least one arom. compd. from a mixt. with at least one aliph. hydrocarbon, which process comprises contacting said mixt. with a salt that is in a liq. state at a temp. below 150°C, said salt having a cation which comprises an arom. nitrogen-contg. heterocyclic ring system, in which a nitrogen atom forming part of said ring system is quaternized and in which said ring system is substituted by at least one electron-withdrawing substituent. Some of said salts are novel. [on SciFinder(R)]
Resumo:
Despite the advances in prostate cancer diagnosis and treatment, current therapies are not curative in a significant proportion of patients. Gene-directed enzyme prodrug therapy (GDEPT), when combined with radiation therapy, could improve the outcome of treatment for prostate cancer, the second leading cause of cancer death in the western world. GDEPT involves the introduction of a therapeutic transgene, which can be targeted to the tumour cells. A prodrug is administered systemically and is converted to its toxic form only in those cells containing the transgene, resulting in cell kill. This review will discuss the clinical trials which have investigated the potential of GDEPT at various stages of prostate cancer progression. The advantages of using GDEPT in combination with radiotherapy will be examined, as well as some of the recent advances which enhance the potential utility of GDEPT.
Resumo:
The present invention relates to a novel class of water compatible molecularly imprinted polymers (AquaMIPs) capable of selectively binding target molecules such as riboflavin, or analogues thereof, in water or aqueous media, their synthesis and use thereof in food processing and extraction or separation processes.
Resumo:
Glibenclamide (GLIB), an oral antidiabetic medication of the sulphonylurea drugs family, was stoichiometrically imprinted using tetrabutylammonium methacrylate as the functional monomer, for the first time in molecular imprinting, and utilising the sulphonylurea affinity for carboxylate anions. Solution association between the drug and the novel functional monomer was studied by 1H-NMR titrations, whereby evidence of sulphonylurea deprotonation followed by the formation of “narcissistic” GLIB dimers was found when tested in CDCl3, while an affinity constant in excess of 105 L mol-1 was measured in DMSO-d6. Detailed analysis of GLIB binding on the subsequently prepared imprinted and non-imprinted polymers confirmed deactivation of binding sites by exchange of a proton between GLIB and methacrylate, followed by extraction of the tetrabutylammonium counterion from the polymer matrix, resulting in overall reduced binding capacities and affinities by the imprinted material under equilibrium conditions. An optimised MI-SPE protocol, which included a binding site re-activation step, was developed for the extraction of GLIB from blood serum, whereby recoveries of up to 92.4% were obtained with exceptional sample clean-up.
Resumo:
The present invention relates to an isolated nucleotide sequence and corresponding polypeptide derived from the nitrile-metabolising Pantoea strain deposited under NCIMB 41854. Said isolated polypeptide acts as a nitrilase and the invention extends to a process for producing a carboxylic acid using said isolated polypeptide to metabolise nitriles such as 3-hydroxyglutaronitrile, 3-hydroxybutyronitrile and 3- hydroxy-phenylpropionitrile to form corresponding carboxylic acids.
Resumo:
This paper uses the history of rubber extraction to explore competing attempts to control the forest environments of Assam and beyond in the second half of the nineteenth century. Forest communities faced rival efforts at environmental control from both European and Indian traders, as well as from various centres of authority within the Raj. Government attempts to regulate rubber collection were undermined by the weak authority of the Raj in these regions, leading to widespread smuggling. Partly in response to the disruptive influence of rubber traders on the frontier, the Raj began to restrict the presence of outsiders in tribal regions, which came to be understood as distinct areas outside British control. When rubber yields from the forests nearest the Brahmaputra fell in the wake of intensive exploitation, India's scientific foresters demanded and from 1870 obtained the ability to regulate the Assamese forests, blaming indigenous rubber tapping strategies for the declining yields and arguing that Indian rubber could be ‘equal [to] if not better' than Amazonian rubber if only tappers would change their practices. The knowledge of the scientific foresters was fundamentally flawed, however, and their efforts to establish a new type of tapping practice failed. By 1880, the government had largely abandoned attempts to regulate wild Indian rubber, though wild sources continued to dominate the supply of global rubber until after 1910.
Resumo:
In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.
Resumo:
In the catalytic hydrogenation of benzene to cyclohexane, the separation of unreacted benzene from the product stream is inevitable and essential for an economically viable process. In order to evaluate the separation efficiency of ionic liquids (ILs) as a solvent in this extraction processes, the ternary (liquid + liquid) equilibrium of 1-alkyl-3-methylimidazolium hexafluorophosphate, [Cnmim][PF6] (n = 4, 5, 6), with benzene and cyclohexane was studied at T = 298.15 K and atmospheric pressure. The reliability of the experimentally determined tie-line data was confirmed by applying the Othmer–Tobias equation. The solute distribution coefficient and solvent selectivity for the systems studied were calculated and compared with literature data for other ILs and sulfolane. It turns out that the benzene distribution coefficient increases and solvent selectivity decreases as the length of the cation alkyl chain grows, and the ionic liquids [Cnmim][PF6] proved to be promising solvents for benzene–cyclohexane extractive separation. Finally, an NRTL model was applied to correlate and fit the experimental LLE data for the ternary systems studied.
Resumo:
Separation of benzene and cyclohexane is one of the most important and difficult processes in the petrochemical industry, especially for low benzene concentration. In this work, three ionic liquids (ILs), [Bmim][BF 4], [Bpy][BF 4], and [Bmim][SCN], were investigated as the solvent in the extraction of benzene from cyclohexane. The corresponding ternary liquid-liquid equilibria (LLE) were experimentally determined at T = 298.15 K and atmospheric pressure. The LLE data were correlated with the nonrandom two-liquid model, and the parameters were fitted. The separation capabilities of the ILs were evaluated in terms of the benzene distribution coefficient and solvent selectivity. The effect of the IL structure on the separation was explained based on a well-founded physical model, COSMO-RS. Finally, the extraction processes were defined, and the operation parameters were analyzed. It shows that the ILs studied are suitable solvents for the extractive separation of benzene and cyclohexane, and their separation efficiency can be generally ranked as [Bmim][BF 4] > [Bpy][BF 4] > [Bmim][SCN]. The extraction process for a feed with 15 mol % benzene was optimized. High product purity (cyclohexane 0.997) and high recovery efficiency (cyclohexane 96.9% and benzene 98.1%) can be reached. © 2012 American Chemical Society.
Resumo:
Learning or writing regular expressions to identify instances of a specific
concept within text documents with a high precision and recall is challenging.
It is relatively easy to improve the precision of an initial regular expression
by identifying false positives covered and tweaking the expression to avoid the
false positives. However, modifying the expression to improve recall is difficult
since false negatives can only be identified by manually analyzing all documents,
in the absence of any tools to identify the missing instances. We focus on partially
automating the discovery of missing instances by soliciting minimal user
feedback. We present a technique to identify good generalizations of a regular
expression that have improved recall while retaining high precision. We empirically
demonstrate the effectiveness of the proposed technique as compared to
existing methods and show results for a variety of tasks such as identification of
dates, phone numbers, product names, and course numbers on real world datasets
Resumo:
AIM: In view of the increased rates of pre-eclampsia observed in diabetic pregnancy and the lack of ex vivo data on placental biomarkers of oxidative stress in T1 diabetic pregnancy, the aim of the current investigation was to examine placental antioxidant enzyme status and lipid peroxidation in pregnant women with type 1 diabetes. A further objective of the study was to investigate the putative impact of vitamin C and E supplementation on antioxidant enzyme activity and lipid peroxidation in type 1 diabetic placentae.
METHODS: The current study measured levels of antioxidant enzyme [glutathione peroxidase (Gpx), glutathione reductase (Gred), superoxide dismutase (SOD) and catalase] activity and degree of lipid peroxidation (aqueous phase hydroperoxides and 8-iso-prostaglandin F2α) in matched central and peripheral samples from placentae of DAPIT (n=57) participants. Levels of vitamin C and E were assessed in placentae and cord blood.
RESULTS: Peripheral placentae demonstrated significant increases in Gpx and Gred activities in pre-eclamptic in comparison to non-pre-eclamptic women. Vitamin C and E supplementation had no significant effect on cord blood or placental levels of these vitamins, nor on placental antioxidant enzyme activity or degree of lipid peroxidation in comparison to placebo-supplementation.
CONCLUSION: The finding that maternal supplementation with vitamin C/E does not augment cord or placental levels of these vitamins is likely to explain the lack of effect of such supplementation on placental indices including antioxidant enzymes or markers of lipid peroxidation.
Resumo:
BACKGROUND: Detection of pre-neoplastic gastric mucosal changes and early gastric cancer (EGC) by white-light endoscopy (WLE) is often difficult. In this study we investigated whether combined autofluorescence imaging (AFI) and narrow band imaging (NBI) can improve detection of pre-neoplastic lesions and early gastric cancer in high-risk patients.
PATIENTS AND METHODS: Chinese patients who were 50-years-old or above with dyspepsia were examined by both high-resolution WLE and combined AFI followed by NBI (AFI-NBI), consecutively in a prospective randomized cross-over setting, by two experienced endoscopists. The primary outcome was diagnostic ability of the two methods for patients with pre-neoplastic lesions such as intestinal metaplasia (IM) and mucosal atrophy.
RESULTS: Sixty-five patients were recruited. One patient with large advanced gastric cancer was found and excluded from the analysis. Among the remaining 64 patients, 38 (59%) had IM; of these, 26 (68%) were correctly identified by AFI-NBI (sensitivity 68%, specificity 23%) and only 13 (34%) by WLE (sensitivity 34%, specificity 65%). AFI-NBI detected more patients with IM than did WLE (p=0.011). Thirty-one patients (48%) had mucosal atrophy. Ten patients (32%) were identified by AFI-NBI (sensitivity 32%, specificity 79%) and four patients (13%) by WLE (sensitivity 13%, specificity 88%) (p=0.100). No dysplasia or EGC was found.
CONCLUSION: AFI-NBI identified significantly more patients with IM than did WLE. Our result warrants further studies to define the role of combined AFI-NBI endoscopy for detection of precancerous conditions.
Resumo:
Enantioenriched and enantiopure thiosulfinates were obtained by asymmetric sulfoxidation of cyclic 1,2-disulfides, using chemical and enzymatic (peroxidase, monooxygenase, dioxygenase) oxidation methods and chiral stationary phase HPLC resolution of racemic thiosulfinates. Enantiomeric excess values, absolute configurations and configurational stabilities of chiral thiosulfinates were determined. Methyl phenyl sulfoxide, benzo[c]thiophene cis-4,5-dihydrodiol and 1,3-dihydrobenzo[c]thiophene derivatives were among unexpected types of metabolites isolated, when acyclic and cyclic 1,2-disulfide were used as substrates for Pseudomonas putida strains. Possible biosynthetic pathways are presented for the production of metabolites from 1,4-dihydrobenzo-2,3-dithiane, including a novel cis-dihydrodiol metabolite that was also derived from benzo[c]thiophene and 1,3-dihydrobenzo[c]thiophene.
Resumo:
The popularity of tri-axial accelerometer data loggers to quantify animal activity through the analysis of signature traces is increasing. However, there is no consensus on how to process the large data sets that these devices generate when recording at the necessary high sample rates. In addition, there have been few attempts to validate accelerometer traces with specific behaviours in non-domesticated terrestrial mammals.