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1.
Chinese Journal of Interventional Imaging and Therapy ; (12): 398-340, 2011.
Article in Chinese | WPRIM | ID: wpr-472677

ABSTRACT

ObjectiveTo explore the clinical application of ultrasound guided percutaneous right internal jugular vein catheterization in hemodialysis,and to analyze the methods,precautions and prevention of complications of puncture.MethodsTotally 297 patients of chronic renal insufficiency with uremia underwent ultrasound guided percutaneous right internal jugular vein catheterization according to technical points of increasing the success rate of puncture.ResultsThe total successful rate of puncture was 100%.The first puncture succeeded in 244 patients (244/297,82.15 %),the second in 30 (30/297,10.10%) and the third in 23 (23/297,7.74%) patients.The complication rate was 15.15% (45/297).Poor adherence of catheter led to cited blood difficultly and inadequate flow in 31 patients.ConclusionUltrasound guidance can greatly improve the success rate of puncture in percutaneous right internal jugular vein catheterization,while reduce the incidence of complications.

2.
Journal of Biomedical Engineering ; (6): 1146-1151, 2010.
Article in Chinese | WPRIM | ID: wpr-260921

ABSTRACT

HLA-A * 0201, HLA-A * 1101, and HLA-A * 2401 CTL restricted epitopes of platelet membrane glycoprotein II b/III a antibody of human and mice were predicted by use of SYFPEITHI, RANKPEP, BIMAS, SVMHC, PREDEP, MHCPRED, and PROPRED predictive programs. In the results, the peptides (found in HLAPRED) that can lead to autoimmune disease and have been published were removed; and the epitopes of HLA-A * 0201 must cover the epitopes of HLA-A * 1101 and HLA-A * 2401 being combined to predTAP and TAPPred for predicting the binding affinity of peptides toward the TAP transporter and NetChop, MAPPP, PAProc for predicting cleavages; HLA-DR Th restricted epitopes of GPII b/III a antibody were predicted by SYFPEITHI, RANKPEP, MHCPRED, and HLAPRED, after removal of the peptides (found in HLAPRED) that can lead to autoimmune disease and have been published, the Th epitopes must cover the CTL mixed epitopes as being stated above. The secondary structure, hydrophobic regions, flexibility, surface probability and the B cell epitope were predicted by using various methods. Ten mixed peptides of T cell epitopes were selected from more than 1 740 peptides. They were located at the aa9-115, aa24-38, aa50-64, aa65-81, aa109-121 of anti-GP II b/III a-Human and the aal-15, aa26-40, aa46-60, aa68-82, aa93-107 of anti-GP II b/III a-Mice. B cell epitopes of anti-GP II b/III a-Human might locate at aa5-9, aa22-30, aa40-46, aa55-71, aa80-90, aa100-105, aa110-115; and the epitopes of anti-GP II b/III a-Human might locate at aa5-10, aa38-43, aa58-70, aa77-84, and aa99-105.


Subject(s)
Animals , Humans , Mice , Antibodies , Allergy and Immunology , Epitopes, B-Lymphocyte , Allergy and Immunology , Epitopes, T-Lymphocyte , Allergy and Immunology , Platelet Glycoprotein GPIIb-IIIa Complex , Allergy and Immunology , Purpura, Thrombocytopenic, Idiopathic , Allergy and Immunology , Vaccines , Allergy and Immunology
3.
Journal of Biomedical Engineering ; (6): 505-510, 2010.
Article in Chinese | WPRIM | ID: wpr-341588

ABSTRACT

p53, as a transcription factor, is an important tumor suppressor gene and plays the key role in the p53-dependent gene regulatory network. Therefore, it is important to understand its biological function at the level of the whole system. In this paper, based on KEGG database and related literatures in English and Chinese, the interaction mode and quantitative relationship of the related molecules involved in p53 signaling pathway were extracted. By using S-system equations and 'Simulink' toolbox of Matlab7.0, a dynamic model of p53 signaling pathway was developed, and the dynamic regulatory characteristics of p53 signaling pathway were analyzed on model simulation. The results were in accord with the literatures and could reflect quantitatively the complex regulatory relationship between the interacting molecules involved in p53 signaling pathway. In addition, model simulation helped us find and identify the key molecules in this signaling pathway. Thus, this model can be used as a basis for the follow-up study of the relationship by precise and quantitative assessment.


Subject(s)
Humans , Algorithms , Computer Simulation , Gene Expression Regulation , Models, Biological , Signal Transduction , Physiology , Transcription Factors , Genetics , Metabolism , Tumor Suppressor Protein p53 , Genetics , Physiology
4.
Chinese Journal of Immunology ; (12)2000.
Article in Chinese | WPRIM | ID: wpr-542071

ABSTRACT

Objective:To develop the mechanistic model for the reorientation of T cell receptors during immunological synapse formation.Methods:Based on the theory of energy transfer during double-molecular reactions in the context of classical fluid mechanics,a vortex-driven model was proposed where in the coupled receptor/ligand molecules within the immunological synapse recruit the T cell receptors.Results:The model results indicated that driven by the consecutive vortexes with specific combinations of strengths and acting frequencies of vortexes,TCR transport speed can reach the values matching up to the experimental measurements(0.04-0.1 ?m/s).Conclusion:The model demonstrated that during the coupling,the membrane-tethered receptor-ligand pairs may transform their binding energies into the rotational energies of the reactants,thereby leading to the vortexes of the surrounding water continuum insider and outside the T cell,and these resulting vortexes may function as the engines for the reorientation of T cell receptors.

5.
Chinese Journal of Pathophysiology ; (12)1989.
Article in Chinese | WPRIM | ID: wpr-524916

ABSTRACT

AIM: To predict MHC class Ⅰ binding peptides by using neural network ensembles. METHODS: As a combination of neural networks, neural network ensemble (NNE) was here used to improve the predictive performance. Based on a database of 628 nonamers and their classified binding capacities, the generalized NNEs were used to classify peptides respectively with non, low, moderate and high binding capacities to MHC class I molecule encoded by gene HLA-A*0201. The predictive power of NNE was further evaluated by running generalized NNE on a set of actual T-cell epitopes. RESULTS: The generalized NNEs achieved an average predictive hit rate of 0.8 for the above classifications. In addition, NNE was also efficient in the prediction of the potential T-cell epitopes, and about 84% of the actual T-cell epitopes were among the potentially antigenic peptides with high and moderate affinities. CONCLUSION: The NNEs can be applied in the prediction of MHC class Ⅰ binding peptides, and moreover, after proper modifications, they can be conveniently extended to cover peptides with any length and thus suitable for the prediction of peptides binding to other MHC class Ⅰ or even class Ⅱ molecules.

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