glycan-node-analysis-a-bottom-up-approach-to-glycomics

Glycan Node Analysis: A Bottom-up Approach to Glycomics

Synthesized in a non-template-driven process by enzymes called glycosyltransferases, glycans are key players in various significant intra- and ...

Arizona State University

The fuzziness in the selection of peritoneal dialysis schemes is discussed. A method of multi-objective fuzzy pattern recognition and its application in the selection of peritoneal dialysis schemes are presented. The method was first applied to the field of peritoneal dialysis. The conclusion showed that this method agreed with doctors' opinions. It provides a new idea for research in this field. At the same time, since the method is simple and easy to use, it can be of wide application.

[Selection of peritoneal dialysis schemes based on multi-objective fuzzy pattern recognition].

Peritoneal dialysis is an important approach to the treatment of renal failure diseases such as acute renal failure, chronic renal failure and uremia. In this paper are presented the application of the multifunction squirm pump developed by authors, the use of PLC and single-chip to control harmonically, and the instituition of full automatic dialysis therapy. Man-machine interface with integrative touch liquid crystal display is adopted in the system, and Chinese interface is used to display and operate so that user can manipulate it in a guiding way. Hence, the whole process is simple and clear. At the same time, it is very easy to set dialysis parameters suited for medical treatment demands of all kinds of patients. Through squirm pump, electric valve, electronic weighing system and electrical heating system, the accurate control of input and output dialysis volumes, flow velocities, temperature, and other parameters are achieved and automatic alarm function is also implemented. Meanwhile, particular intelligent card system that can access automatically the user's treatment information is syncretized, which is convenient for doctor to make a diagnosis and give treatment or to carry out remote treatment. This system plays an important role in the improvement of peritoneal dialysis technique for renal failure treatment and clinical implementation.

[Intelligent peritoneal dialysis system for the treatment of renal failure].

Against the large number of assessment indices to the adequacy peritoneal dialysis and incompatibility of some indices, an intelligent assessment approach to the peritoneal dialysis adequacy based on MART2 (modified from ART2) network is proposed. After non-dimension and weighting preconditioning, the assessment indices were put to MART2 and sorted into many clusters. The center-of-gravity of each cluster was identified as adequacy or inadequacy according to the assessment criteria of dialysis adequacy, and the adequacy of each cluster could be determined by the adequacy of corresponding center-of-gravity when the network threshold was high. Finally, the peritoneal dialysis adequacy of each patient could be judged according to the adequacy of cluster to which the patients' indices belong. Experimental results demounstrate its effectiveness.

[An assessment approach to the adequacy of peritoneal dialysis based on modified MART2 network].

This paper addresses the predicting problem of peritoneal fluid absorption rate(PFAR). An innovative predicting model was developed, which employed the improved genetic algorithm embedded in neural network for predicting the important PFAR index in the peritoneal dialysis treatment process of renal failure. The significance of PFAR and the complexity of dialysis process were analyzed. The improved genetic algorithm was used for defining the initial weight and bias of neural network, and then the neural network was used for finding out the optimal predicting model of PFAR. This method utilizes the global search capability of genetic algorithm and the local search advantage of neural network completely. For the purpose of showing the validity of the model, the improved optimal predicting model is compared with the standard hybrid method of genetic algorithm and neural network. The simulation results show that the predicting accuracy of the improved optimal neural network is greatly improved and the learning process needs less time.

[An optimal predicting method based on improved genetic algorithm embedded in neural network and its application to peritoneal dialysis].

The present paper discusses the relationship between the coverage fraction of submerged plants and the observed spectral characteristics. The purpose of this paper is to validate a remote sensing technology to monitor the change in the plant composition of a water body. In the current study, the reflectance spectra of the submerged plant Vallisneria spiralis at different fraction coverages of the wetland in Hangzhou Bay were measured. The relationships between the fraction coverage of V. spiralis and simulated Quickbird normalized difference vegetation index (NDVI), red edge, and other spectral characteristic parameters were established. The results showed that the spectral reflectance characteristics of submerged plant V. spiralis were mainly in the visible light (490-650 nm) and near infrared (700-900 nm). The rate of change of the blue band curve and simulated Quickbird NDVI showed a higher correlation with the V. spiralis coverage, so estimation models of the fraction coverage were constructed using these parameters. The estimated fraction coverage of V. spiralis with different models were validated with ground data, and the accuracy of estimation models was assessed. The most suitable estimated fraction coverage of V. spiralis was obtained using the rate of change of the blue band curve and simulated Quickbird NDVI. The present work demonstrated a method to monitor the distribution and dynamical variation of submerged plants at the large scale.

Research on the relationship between the fractional coverage of the submerged plant Vallisneria spiralis and observed spectral parameters.

The effect of dynamic high pressure microfluidisation (DHPM) pretreatment on the glycation of bovine serum albumin (BSA) was investigated. A detailed glycation map was obtained from high resolution mass spectrometry. Without DHPM pretreatment, only 7 glycation sites were identified, whereas the numbers were increased to 10, 11 and 11 when BSA-glucose was pretreated with DHPM at 50, 100 and 200 MPa, respectively, suggesting that DHPM pretreatment can significantly promote the Maillard reaction. Average degree of substitution per peptide molecule BSA (DSP) was used to further evaluate the glycation level under various DHPM conditions. All the DHPM pretreated samples exhibited elevated glycation level compared to the un-pretreated sample. With 100 MPa DHPM pretreatment, the protein showed the most significantly enhanced glycation extent. In addition, our results suggest that Maillard-type glycation followed by mass spectrometry analysis can be used to study the conformational changes when proteins are disturbed by external forces.

Glycation promoted by dynamic high pressure microfluidisation pretreatment revealed by high resolution mass spectrometry.

In vitro studies have shown that LEA proteins from plants and invertebrates protect and stabilise other proteins under conditions of water stress, suggesting a role in stress tolerance. However, there is little information on LEA protein function in whole plants or plant cells, particularly with respect to their anti-aggregation activity. To address this, we expressed in tobacco BY-2 suspension cells an aggregation-prone protein based on that responsible for Huntington's disease (HD). In HD, abnormally long stretches of polyglutamine (polyQ) in huntingtin (Htt) protein cause aggregation of Htt fragments within cells. We constructed stably transformed BY-2 cell lines expressing enhanced green fluorescent protein (EGFP)-HttQ23 or EGFP-HttQ52 fusion proteins (encoding 23 or 52 glutamine residues, pertaining to the normal and disease states, respectively), as well as an EGFP control. EGFP-HttQ52 protein aggregated in the cytoplasm of transformed tobacco cells, which showed slow growth kinetics; in contrast, EGFP-HttQ23 or EGFP did not form aggregates and cells expressing these constructs grew normally. To test the effect of LEA proteins on protein aggregation in plant cells, we constructed cell lines expressing both EGFP-HttQ52 and LEA proteins (PM1, PM18, ZLDE-2 or AavLEA1) or a sHSP (PM31). Of these, AavLEA1 and PM31 reduced intracellular EGFP-HttQ52 aggregation and alleviated the associated growth inhibition, while PM18 and ZLDE-2 partially restored growth rates. Treatment of EGFP-HttQ52-expressing BY2 cells with the polyphenol epigallocatechin-3-gallate (EGCG) also reduced EGFP-HttQ52 aggregation and improved cell growth rate. The EGFP-HttQ52 cell line therefore has potential for characterising both macromolecular and small molecule inhibitors of protein aggregation in plant cells.

A plant cell model of polyglutamine aggregation: Identification and characterisation of macromolecular and small-molecule anti-protein aggregation activity in vivo.

In view of the fact that medical inspection equipment sold in the domestic market is mainly imported from abroad and very expensive, we developed a full-automatic fluorescence analyzer in our center, presented in this paper. The present paper introduces the hardware architecture design of FPGA/DSP motion controlling card+PC+ STM32 embedded micro processing unit, software system based on C# multi thread, design and implementation of double-unit communication in detail. By simplifying the hardware structure, selecting hardware legitimately and adopting control system software to object-oriented technology, we have improved the precision and velocity of the control system significantly. Finally, the performance test showed that the control system could meet the needs of automated fluorescence analyzer on the functionality, performance and cost.

Yueming Hu

Department of Chemistry & Biochemistry,
The Biodesign Institute – Center for Personalized Diagnostics,
Department of Chemistry & Biochemistry, The Biodesign Institute – Center for Personalized Diagnostics

Arizona State University

Glycan Node Analysis: A Bottom-up Approach to Glycomics

Yueming Hu

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Chemistry & Biochemistry,The Biodesign Institute – Center for Personalized Diagnostics,Department of Chemistry & Biochemistry, The Biodesign Institute – Center for Personalized Diagnostics

Arizona State University

Glycan Node Analysis: A Bottom-up Approach to Glycomics

Department of Chemistry & Biochemistry,
The Biodesign Institute – Center for Personalized Diagnostics,
Department of Chemistry & Biochemistry, The Biodesign Institute – Center for Personalized Diagnostics