828 resultados para Blind
Resumo:
To extend the cross-hole seismic 2D data to outside 3D seismic data, reconstructing the low frequency data to high frequency data is necessary. Blind deconvolution method is a key technology. In this paper, an implementation of Blind deconvolution is introduced. And optimized precondition conjugate gradient method is used to improve the stability of the algorithm and reduce the computation. Then high-frequency retrieved Seismic data and the cross-hole seismic data is combined for constraint inversion. Real data processing proved the method is effective. To solve the problem that the seismic data resolution can’t meet the request of reservoir prediction in the river face thin-layers in Chinese eastern oil fields, a high frequency data reconstruction method is proposed. The extrema of the seismic data are used to get the modulation function which operated with the original seismic data to get the high frequency part of the reconstruction data to rebuild the wide band data. This method greatly saves the computation, and easy to adjust the parameters. In the output profile, the original features of the seismic events are kept, the common feint that breaking the events and adding new zeros to produce alias is avoided. And the interbeded details are enhanced compared to the original profiles. The effective band of seismic data is expended and the method is approved by the processing of the field data. Aim to the problem in the exploration and development of Chinese eastern oil field that the high frequency log data and the relative low frequency seismic data can’t be merged, a workflow of log data extrapolation constrained by time-phase model based on local wave decomposition is raised. The seismic instantaneous phase is resolved by local wave decomposition to build time-phase model, the layers beside the well is matched to build the relation of log and seismic data, multiple log info is extrapolated constrained by seismic equiphase map, high precision attributes inverse sections are produced. In the course of resolve the instantaneous phase, a new method of local wave decomposition --Hilbert transform mean mode decomposition(HMMD) is raised to improve the computation speed and noise immunity. The method is applied in the high resolution reservoir prediction in Mao2 survey of Daqing oil field, Multiple attributes profiles of wave impedance, gamma-ray, electrical resistivity, sand membership degree are produced, of which the resolution is high and the horizontal continuous is good. It’s proved to be a effective method for reservoir prediction and estimation.
Resumo:
Geothermal resource is rich in Guanzhong Basin, but as to its cycle characteristic, there has been lack of systematic study so far. Blind exploitations lead to water-temperature reducing, the decrease of spring flow rate and so on. Based on groundwater system and hydrogeological and hydrological geochemical theory, this paper studied the recycling type of geothermal water and analyzed the resources of dissolved inorganic carbon (DIC) and sulfate. The origin of the internal geothermal water is ice and snow in Qinling Mountain and Liupan Mountain above 1400m. The precipitation and surface water entered the deep part of the basin along piedmont faults, heated and water-expansion increased. The karst groundwater comes from meteoric water of the bare carbonate rock area in the North Mountains. Geothermal-water DIC mainly came from the dissolution of carbonate rock in the deep part of Guanzhong Basin, sulfate of Xi’an depression and Lishan salient came from the dissolution of continental evaporate , and sulfate of Gushi depression and Xianli salient came from co-dissolution of continental and marine evaporate. The above results supply science basis for reasonable exploitation and sustainable utilization of the geothermal water in Guanzhong Basin.
Resumo:
Reflectivity sequences extraction is a key part of impedance inversion in seismic exploration. Although many valid inversion methods exist, with crosswell seismic data, the frequency brand of seismic data can not be broadened to satisfy the practical need. It is an urgent problem to be solved. Pre-stack depth migration which developed in these years becomes more and more robust in the exploration. It is a powerful technology of imaging to the geological object with complex structure and its final result is reflectivity imaging. Based on the reflectivity imaging of crosswell seismic data and wave equation, this paper completed such works as follows: Completes the workflow of blind deconvolution, Cauchy criteria is used to regulate the inversion(sparse inversion). Also the precondition conjugate gradient(PCG) based on Krylov subspace is combined with to decrease the computation, improves the speed, and the transition matrix is not necessary anymore be positive and symmetric. This method is used to the high frequency recovery of crosswell seismic section and the result is satisfactory. Application of rotation transform and viterbi algorithm in the preprocess of equation prestack depth migration. In equation prestack depth migration, the grid of seismic dataset is required to be regular. Due to the influence of complex terrain and fold, the acquisition geometry sometimes becomes irregular. At the same time, to avoid the aliasing produced by the sparse sample along the on-line, interpolation should be done between tracks. In this paper, I use the rotation transform to make on-line run parallel with the coordinate, and also use the viterbi algorithm to complete the automatic picking of events, the result is satisfactory. 1. Imaging is a key part of pre-stack depth migration besides extrapolation. Imaging condition can influence the final result of reflectivity sequences imaging greatly however accurate the extrapolation operator is. The author does migration of Marmousi under different imaging conditions. And analyzes these methods according to the results. The results of computation show that imaging condition which stabilize source wave field and the least-squares estimation imaging condition in this paper are better than the conventional correlation imaging condition. The traditional pattern of "distributed computing and mass decision" is wisely adopted in the field of seismic data processing and becoming an obstacle of the promoting of the enterprise management level. Thus at the end of this paper, a systemic solution scheme, which employs the mode of "distributed computing - centralized storage - instant release", is brought forward, based on the combination of C/S and B/S release models. The architecture of the solution, the corresponding web technology and the client software are introduced. The application shows that the validity of this scheme.
Resumo:
The dissertation addressed the problems of signals reconstruction and data restoration in seismic data processing, which takes the representation methods of signal as the main clue, and take the seismic information reconstruction (signals separation and trace interpolation) as the core. On the natural bases signal representation, I present the ICA fundamentals, algorithms and its original applications to nature earth quake signals separation and survey seismic signals separation. On determinative bases signal representation, the paper proposed seismic dada reconstruction least square inversion regularization methods, sparseness constraints, pre-conditioned conjugate gradient methods, and their applications to seismic de-convolution, Radon transformation, et. al. The core contents are about de-alias uneven seismic data reconstruction algorithm and its application to seismic interpolation. Although the dissertation discussed two cases of signal representation, they can be integrated into one frame, because they both deal with the signals or information restoration, the former reconstructing original signals from mixed signals, the later reconstructing whole data from sparse or irregular data. The goal of them is same to provide pre-processing methods and post-processing method for seismic pre-stack depth migration. ICA can separate the original signals from mixed signals by them, or abstract the basic structure from analyzed data. I surveyed the fundamental, algorithms and applications of ICA. Compared with KL transformation, I proposed the independent components transformation concept (ICT). On basis of the ne-entropy measurement of independence, I implemented the FastICA and improved it by covariance matrix. By analyzing the characteristics of the seismic signals, I introduced ICA into seismic signal processing firstly in Geophysical community, and implemented the noise separation from seismic signal. Synthetic and real data examples show the usability of ICA to seismic signal processing and initial effects are achieved. The application of ICA to separation quake conversion wave from multiple in sedimentary area is made, which demonstrates good effects, so more reasonable interpretation of underground un-continuity is got. The results show the perspective of application of ICA to Geophysical signal processing. By virtue of the relationship between ICA and Blind Deconvolution , I surveyed the seismic blind deconvolution, and discussed the perspective of applying ICA to seismic blind deconvolution with two possible solutions. The relationship of PC A, ICA and wavelet transform is claimed. It is proved that reconstruction of wavelet prototype functions is Lie group representation. By the way, over-sampled wavelet transform is proposed to enhance the seismic data resolution, which is validated by numerical examples. The key of pre-stack depth migration is the regularization of pre-stack seismic data. As a main procedure, seismic interpolation and missing data reconstruction are necessary. Firstly, I review the seismic imaging methods in order to argue the critical effect of regularization. By review of the seismic interpolation algorithms, I acclaim that de-alias uneven data reconstruction is still a challenge. The fundamental of seismic reconstruction is discussed firstly. Then sparseness constraint on least square inversion and preconditioned conjugate gradient solver are studied and implemented. Choosing constraint item with Cauchy distribution, I programmed PCG algorithm and implement sparse seismic deconvolution, high resolution Radon Transformation by PCG, which is prepared for seismic data reconstruction. About seismic interpolation, dealias even data interpolation and uneven data reconstruction are very good respectively, however they can not be combined each other. In this paper, a novel Fourier transform based method and a algorithm have been proposed, which could reconstruct both uneven and alias seismic data. I formulated band-limited data reconstruction as minimum norm least squares inversion problem where an adaptive DFT-weighted norm regularization term is used. The inverse problem is solved by pre-conditional conjugate gradient method, which makes the solutions stable and convergent quickly. Based on the assumption that seismic data are consisted of finite linear events, from sampling theorem, alias events can be attenuated via LS weight predicted linearly from low frequency. Three application issues are discussed on even gap trace interpolation, uneven gap filling, high frequency trace reconstruction from low frequency data trace constrained by few high frequency traces. Both synthetic and real data numerical examples show the proposed method is valid, efficient and applicable. The research is valuable to seismic data regularization and cross well seismic. To meet 3D shot profile depth migration request for data, schemes must be taken to make the data even and fitting the velocity dataset. The methods of this paper are used to interpolate and extrapolate the shot gathers instead of simply embedding zero traces. So, the aperture of migration is enlarged and the migration effect is improved. The results show the effectiveness and the practicability.
Resumo:
With the progress of prospecting, the need for the discovery of blind ore deposits become more and more urgent. To study and find out the method and technology for the discovery of blind and buried ores is now a priority task. New geochemical methods are key technology to discover blind ores. Information of mobile components related to blind ores were extracted using this new methods. These methods were tested and applied based on element' s mobile components migrating and enriched in geophysical-geochemical process. Several kinds of partial extraction techniques have tested based on element' s occurrence in hypergenic zone. Middle-large scale geochemical methods for exploration in forest and swamp have been tested. A serious of methods were tested and applied effetely about evaluation of regional geochemical anomaly, 1:25000 bedrock or soil geochemical methods sampling based on the net in dendritic water system instead of the normal net. 1. Element related with ores can be mobiled to migrate upwards and be absorpted by surface soil. These abnomal components can be concentrated by natural or artificial methods. These trace metalic ions partially exist in dissovlvable ion forms of active state, and partially have been absorbed by Fe-Mn oxide, soil and organic matter in the soil so that a series of reaction such as complex reaction have take place. Employing various partial extraction techniques, metallic ions related with the phase of the blind ores can be extracted, such as the technique of organic complex extraction, Fe-Mn oxide extraction and the extraction technique of metallic ions of various absorption phases. 2.1:200000 regional geochemical evaluation anomaly methods: Advantageous ore-forming areas were selected firstly. Center, concentration, morphological feature, belt of anomaly were choosed then. Geological and geochemical anomalies were combined. And geological and geochemical background information were restrained. Xilekuduke area in Fuyun sheet , Zhaheba area in Qiakuerte sheet, the west-north part in Ertai sheet and Hongshanzui anomaly in Daqiao sheet were selected as target areas, in Alertai, in the north of Xinjiang. in Xilekuduke area, 1:25000 soil geochemical methods sampling based on the net in dendritic water system was carried out. Cu anomaly and copper mineralization were determined in the center area. Au , Cu anomalies and high polarization anomaly were determined in the south part. Prospecting by primary halo and organic complex extraction were used to prognosis blind ore in widely rang outcrop of bedrock. 1:25000 bedrock or soil geochemical methods sampling based on the net in dendritic water system were used in transported overburden outside of mining area. Shallow seismic method and primary halo found a new blind orebody in mining area. A mineralization site was fou and outside of Puziwan gold mine, in the north of Shanxi province. Developing middle-large scale geochemical exploration method is a key technique based 1:200000 regional geochemical exploration. Some conditions were tested as Sampling density , distribution sites of sample, grain size of sample and occurrence of element for exploration. 1:50000 exploration method was advanced to sample clast sediment supplement clast sediment in valley. 1:25000 bedrock or soil geochemical methods sampling based on the net in dendritic water system was applied to sample residual material in A or C horizon. 1:2000 primary or soil halo methods used to check anomalies and determine mineralization. Daliang gold mineralization in the northern Moerdaoga was found appling these methods. Thermomagnetic method was tested in miniqi copper-polymetallic ore. Process methods such as grain size of sample, heated temperature, magnetic separating technique were tested. A suite of Thermomagnetic geochemical method was formed. This method was applied in Xiangshan Cu~Ni deposit which is cover by clast or Gobi in the eastern Xinjiang. Element's content and contrast of anomaly with Thermomagnetic geochemical method were higher than soil anomaly. Susceptibility after samples were heated could be as a assessment conference for anomaly. In some sectors thermo-magnetic Cu, Ni, Ti anomalious were found outside deposits area. There were strong anomal ies response up ore tested by several kind of partial extraction methods include Thermomagnetic, enzyme leach and other partial extractions in Kalatongke Cu-Ni deposit in hungriness area in the northern of Xinjiang. Element's anomalies of meobile were mainly in Fe-Mn oxide and salt. A Copper mineralization site in Xilekuduke anomaly area had been determined. A blind ore was foung by shallow seismic and geochemical method and a mineralization site was found outside this mining area in Puziwan gold deposit in shanxi province. A Gold mineralization site was found by 1:50000 geochemical exploration in Daliang, Inner Mongolia.
Resumo:
Davison, G. and Gleeson, M. (2005). Influence of Acute Vitamin C and/or Carbohydrate Ingestion on Hormonal, Cytokine, and Immune Responses to Prolonged Exercise. International Journal of Sport Nutrition and Exercise Metabolism. 15(5), pp.465-479 RAE2008
Resumo:
People with sight loss in the United Kingdom are known to have lower levels of emotional wellbeing and to be at higher risk of depression. Consequently ‘having someone to talk to’ is an important priority for people with visual impairment. An on-line survey of the provision of emotional support and counselling for people affected by sight loss across the UK was undertaken. The survey was distributed widely and received 182 responses. There were more services offering ‘emotional support’, in the form of listening and information and advice giving, than offered ‘counselling’. Services were delivered by providers with differing qualifications in a variety of formats. Waiting times were fairly short and clients presented with a wide range of issues. Funding came from a range of sources, but many felt their funding was vulnerable. Conclusions have been drawn about the need for a national standardised framework for the provision of emotional support and counselling services for blind and partially sighted people in the UK
Resumo:
Chapter is an attempt at reconstruction of the culminating moment of the first stage of the Polish reception of Shakespeare's "Hamlet". It has been entirely devoted to J. Słowacki's "Horsztyński". There is no doubt that "Horsztyński" should be viewed as the fullest and deepest interpretation of Shakespearean elements in the literary output of Juliusz Słowacki. Numerous citations and references to the works of the Elizabethan dramatist reach deeply into the structure of the world and human's life. Thanks to many adductions (citations) to Shakespeare, Słowacki approached the so much important problem for the Romantic period in Polish literature, namely the problem of individual tragedy of existence of the main character of a play and a clash with historical dilemmas of the community. The analysis of the text is aimed at showing all references to Shakespearean masterpiece with a particular emphasis on the hamletism of the charactwe of Szczęsny Kossakowski. The author describes the motif of betrayal, ever-present on different levels of the text structure, which in the most complete way describes the organisation of space between humans and their interaction in "Horsztyński". The author focuses his attention on detailed description and analysis of the recurrent themes frequently repeated in Szczęsny's statements, namely motifs of "man-harp", "man-actor in the theatre of the world", and "man-puppet", harlequin, clown. These motifs prove the sensibility of Szczęsny's to the theatrical aspect of the surrounding reality. The motif of darkness and of a blind man groping his way in the darkness so frequent in Szczęsny's statements can be interpreted as a manifestation of utter lack of hope and the feeling of uselessness of one's existence in the world.
Resumo:
A neural network is introduced which provides a solution of the classical motor equivalence problem, whereby many different joint configurations of a redundant manipulator can all be used to realize a desired trajectory in 3-D space. To do this, the network self-organizes a mapping from motion directions in 3-D space to velocity commands in joint space. Computer simulations demonstrate that, without any additional learning, the network can generate accurate movement commands that compensate for variable tool lengths, clamping of joints, distortions of visual input by a prism, and unexpected limb perturbations. Blind reaches have also been simulated.
Resumo:
This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.
Resumo:
Increased plasmin and plasminogen levels and elevated somatic cell counts (SCC) and polymorphonuclear leucocyte levels (PMN) were evident in late lactation milk. Compositional changes in these milks were associated with increased SCC. The quality of late lactation milks was related to nutritional status of herds, with milks from herds on a high plane of nutrition having composition and clotting properties similar to, or superior to, early-mid lactation milks. Nutritionally-deficient cows had elevated numbers of polymorphonuclear leucocytes (PMNs) in their milk, elevated plasmin levels and increased overall proteolytic activity. The dominant effect of plasmin on proteolysis in milks of low SCC was established. When present in elevated numbers, somatic cells and PMNs in particular had a more significant influence on the proteolysis of both raw and pasteurised milks than plasmin. PMN protease action on the caseins showed proteolysis products of two specific enzymes, cathepsin B and elastase, which were also shown in high SCC milk. Crude extracts of somatic cells had a high specificity on αs1-casein. Cheeses made from late lactation milks had increased breakdown of αs1-casein, suggestive of the action of somatic cell proteinases, which may be linked to textural defects in cheese. Late lactation cheeses also showed decreased production of small peptides and amino acids, the reason for which is unknown. Plasmin, which is elevated in activity in late lactation milk, accelerated the ripening of Gouda-type cheese, but was not associated with defects of texture or flavour. The retention of somatic cell enzymes in cheese curd was confirmed, and a potential role in production of bitter peptides identified. Cheeses made from milks containing high levels of PMNs had accelerated αs1-casein breakdown relative to cheeses made from low PMN milk of the same total SCC, consistent with the demonstrated action of PMN proteinases. The two types of cheese were determined significantly different by blind triangle testing.
Resumo:
The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.
Resumo:
The objective of my Portfolio is to explore the working hypothesis that the organic growth of a firm is governed by the perspectives of individuals and such perspectives are governed by their meaning-making. The Portfolio presents explorations of the transformation of my meaning making and in adopting new practices to support the organic growth of a firm. I use the work of other theorists to transition my understanding of how the world works. This transition process is an essential tool to engage with and understand the perspectives of others and develop a mental capacity to “train one’s imagination to go visiting” (Arendt, 1982; p.43). The Portfolio, therefore, is primarily located in reflective research. Using Kegan’s (1994) approach to Adult Mental Development, and Sowell’s (2007) understanding of the visions which silently shape our thoughts I organise the developments of my meaning making around three transformation pillars of change. In pillar one I seek to transform an unthinking respect for authority and break down a blind pervasiveness of thought within my reasoning process arising from an instinct for attachment and support from others whom I trust. In pillar two I seek to discontinue using autocratic leadership and learn to use the thoughts and contributions of a wider team to make improved choices about uncertain future events. In pillar three I explore the use of a more reflective thinking framework to test the accuracy of my perceptions and apply a high level of integrity in my reasoning process. The transformation of my meaning making has changed my perspectives and in turn my preferred practices to support the organic growth of a firm. I identify from practice that a transformative form of leadership is far more effective that a transactional form of leadership to stimulate the trust and teamwork required to sustain the growth a firm. Creating an environment where one feels free to share thoughts and feelings with others is an essential tool to build a team to critique the thoughts of one other. Furthermore, the entrepreneurial wisdom to grow a firm must come from a wider team, located both inside and outside the boundaries of a firm. No individual or small team has the mental capacity to provide the entrepreneurship required to drive the organic growth of a firm. I address my Portfolio to leaders in organisations who have no considered framework on the best practices required to lead a social organisation. These individuals may have no sense of what they implicitly believe drives social causation and they may have no understanding if their meaning making supports or curtails the practices required to grow a firm. They may have a very limited capacity to think in a logical manner, with the result they are using guesses from their ‘gut’ to make poor judgements in the management of a firm.
Resumo:
BACKGROUND & AIMS: Prophylactic administration of interleukin (IL)-10 decreases the severity of experimental pancreatitis. Prevention of post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis in humans is a unique model to study the potential role of IL-10 in this setting. METHODS: In a single-center, double-blind, randomized, placebo-controlled study, the effect of a single injection of 4 microg/kg (group 1) or 20 microg/kg (group 2) IL-10 was compared with that of placebo (group 0), all administered 30 minutes before therapeutic ERCP. The primary endpoint was the effect of IL-10 on serum levels of amylases and lipases measured 4, 24, and 48 hours after ERCP. The secondary objective was to evaluate changes in plasma cytokines (IL-6, IL-8, tumor necrosis factor) at the same time points and the incidence of acute pancreatitis in the 3 groups. Subjects undergoing a first therapeutic ERCP were eligible for inclusion. RESULTS: A total of 144 patients were included. Seven were excluded based on intention to treat (n = 1) or per protocol (n = 6). Forty-five, 48, and 44 patients remained in groups 0, 1, and 2, respectively. The 3 groups were comparable for age, sex, underlying disease, indication for treatment, type of treatment, and plasma levels of C-reactive protein (CRP), cytokines, and hydrolases at baseline. No significant difference was observed in CRP, cytokine, and hydrolase plasma levels after ERCP. Forty-three patients developed hyperhydrolasemia (18 in group 0, 14 in group 1, and 11 in group 2; P = 0.297), and 19 patients developed acute clinical pancreatitis (11 in group 0, 5 in group 1, 3 in group 2; P = 0.038). Two severe cases were observed in the placebo group. No mortality related to ERCP was observed. Logistic regression identified 3 independent risk factors for post-therapeutic ERCP pancreatitis: IL-10 administration (odds ratio [OR], 0.46; 95% confidence interval [95% CI], 0.22-0.96; P = 0.039), pancreatic sphincterotomy (OR, 5.04; 95% CI, 1.53-16.61; P = 0.008), and acinarization (OR, 8.19; 95% CI, 1.83-36.57; P = 0.006). CONCLUSIONS: A single intravenous dose of IL-10, given 30 minutes before the start of the procedure, independently reduces the incidence of post-therapeutic ERCP pancreatitis.
Resumo:
To compare the incidence and timing of bone fractures in postmenopausal women treated with 5 years of adjuvant tamoxifen or letrozole for endocrine-responsive early breast cancer in the Breast International Group (BIG) 1-98 trial.