scholarly journals Stoichiometric Relationship between Na+ Ions Transported and Glucose Consumed in Human Erythrocytes: Bayesian Analysis of 23Na and 13C NMR Time Course Data

2013 ◽  
Vol 104 (8) ◽  
pp. 1676-1684 ◽  
Author(s):  
Max Puckeridge ◽  
Bogdan E. Chapman ◽  
Arthur D. Conigrave ◽  
Stuart M. Grieve ◽  
Gemma A. Figtree ◽  
...  
1993 ◽  
Vol 296 (2) ◽  
pp. 379-387 ◽  
Author(s):  
H A Berthon ◽  
W A Bubb ◽  
P W Kuchel

13C double-quantum filtered correlation spectroscopy (DQF-COSY) provides a novel method for the detection of reactions involving carbon-bond scissions. We report the use of this technique to investigate isotopic exchange reactions of the non-oxidative pentose phosphate pathway in human erythrocytes. These exchange reactions resulted in the formation of a range of isotopic isomers (isotopomers) of glucose 6-phosphate after incubation of a mixture of universally 13C-labelled and unlabelled glucose 6-phosphate with fructose 1,6-bisphosphate and haemolysates. These isotopomers were detected in the coupling patterns of cross-peaks within the DQF-COSY spectrum of the deproteinized sample. A computer model which fully describes the reactions of the non-oxidative pentose phosphate pathway in human erythrocytes has previously been constructed and tested with 31P n.m.r. time-course data in our laboratory. This model was refined using 13C n.m.r. time-course data and extended to include the range of isotopomers which may be formed experimentally by the reactions of the non-oxidative pentose phosphate pathway. The isotopomer ratios obtained experimentally from the DQF-COSY spectrum were consistent with simulations generated by this model.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Arika Fukushima ◽  
Masahiro Sugimoto ◽  
Satoru Hiwa ◽  
Tomoyuki Hiroyasu

Abstract Background Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary. Results We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS. Conclusions The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.


2017 ◽  
Vol 14 (2) ◽  
Author(s):  
Qihua Tan ◽  
Mads Thomassen ◽  
Mark Burton ◽  
Kristian Fredløv Mose ◽  
Klaus Ejner Andersen ◽  
...  

AbstractModeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.


1980 ◽  
Vol 188 (2) ◽  
pp. 535-540 ◽  
Author(s):  
A Tomoda ◽  
M Ida ◽  
A Tsuji ◽  
Y Yoneyama

The time course of methaemoglobin reduction in human erythrocytes treated with nitrite was studied at pH 7.4, 37 degrees C, in the presence or absence of Methylene Blue, and the changes in methaemoglobin, intermediate haemoglobins and oxyhaemoglobin during the reaction were analysed by isoelectric-focusing on Ampholine/polyacrylamide-gel plates. In both cases, with or without the dye, the intermediate haemoglobins were found to be present at (alpha 3+beta 2+)2 and (alpha 2+beta 3+)2 valency hybrids from their characteristic position on electrophoresis, but amounts changed consecutively with time. The amount of (alpha 3+beta 2+)2 was always greater than that of the (alpha 2+beta 3+)2 valency hybrid. This result is explained by the differences in redox potentials between alpha- and beta-chains in methaemoglobin tetramer. It was concluded that methaemoglobin was reduced in human erythrocytes through these two different pats: methaemoglobin leads to k+3 (alpha 2+beta 3+)2 leads to k+3 oxyhaemoglobin. The reaction rate constants k'+1 (= k+1+k+3) and k'+2(=k+2+k+4) were estimated from the changes in each component methaemoglobin, intermediate haemoglobins [(alpha 3+beta 2+)2+(alpha 2+beta 3+)2] and oxyhaemoglobin.


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