Human Mesenchymal Stem Cells Elevate CD4+CD25+CD127low/- Regulatory T Cells of Asthmatic Patients via Heme Oxygenase-1
Abstract
Up-regulation of CD4+CD25+CD127low/- regulatory T cells (Tregs) is a new target in the treatment of asthma. Human bone marrow mesenchymal stem cells can up-regulate CD4+CD25+CD127low/- regulatory T cells in vitro, meanwhile, heme oxygenase-1 (HO-1) plays an important role in the development and maintenance of CD4+CD25+ regulatory T cells. However the mechanism has not yet been adequately understood. Hence, we wondered what effect of Heme Oxygenase-1 made on regulation of CD4+CD25+CD127low/- regulatory T cells mediated by mesenchymal stem cells.
Peripheral blood mononuclear cells isolated from asthmatic patients and healthy controls were co-cultured with human bone marrow mesenchymal stem cells which were pretreated with Hemin (the revulsive of Heme Oxygenase-1), Protoporphyrin Ⅸ zinc (the inhibitor of Heme Oxygenase-1) and saline.
The expression of Heme Oxygenase-1 in MSCs was enhanced by Hemin and inhibited by Protoporphyrin zinc in vitro. Overexpression of Heme Oxygenase-1 elevated the proportion of CD4+CD25+CD127low/- regulatory T cells in CD4+ T cells, meanwhile, inhibition of Heme Oxygenase-1 decreased the proportion of CD4+CD25+CD127low/- regulatory T cells in CD4+ T cells as compared with mesenchymal stem cells alone.
Taken together, these data demonstrated that Heme Oxygenase-1 contributed to the up-regulation of CD4+CD25+CD127low/- regulatory T cells mediated by mesenchymal stem cells in asthma.
1. Steven E. Weinberger, Barbara A. Cockrill, Jess Mandel, Principles of pulmonary medicine, 5th Ed., Elsevier Inc,2008.
2. Rhoades C, Thomas F. Capnography: beyond the numbers. Air Med J 2002; 21(2):43-8.
3. Giner J, Casan P. Pulse Oximetry and Capnography in Lung Function Laboratories. Arch Bronconeumol 2004;40(7):311-4.
4. Thompson JE, Jaffe MB. Capnography waveforms in the mechanically ventilated patient. Respir Care 2005;50(1):100-9.
5. Smalhout B., Kalenda Z., An Atlas of Capnography, 2nd Ed., Kerckebosche Zeist Press, 1981.
6. You B, Peslin R, Duvivier C, Vu V, Grilliat JP.Expiratory capnography in asthma. Eur Respir J 1994: 7(2):318-23.
7. Yaron M, Padyk P, Hutsinpiller M, Cairns CB. Utility of the expiratory capnogram in the assessment of bronchospasm. Ann Emerg Med 1996; 28(4):403-7.
8. Druck J, Rubio PM, Valley MA, Jaffe MB, Yaron M.Evaluation of the slope of phase III from the volumetric capnogram as a non-effort dependent in acute asthma exacerbation. Annual of Emergency Medicine 2007;50(3):130-6.
9. Tan Teik Kean, M. B. Malarvili. Analysis of capnography for asthmatic patient, IEEE International Conference on Signal and Image Processing Applications 2009: 464-7.
10. Swenson J, Henao-Guerrero PN, Carpenter JW. Clinical Technique: Use of Capnography in Small Mammal Anesthesia. Journal of Exotic Pet Medicine 2008:17(3):175-80.
11. Kirkko-Jaakkola M, Collin J, Takala J. Bias Prediction for MEMS Gyroscopes, IEEE Sensors 2012; 12(6):2157-63.
12. Facchinetti A, Sparacino G, Cobelli C. An Online Self- Tunable Method to Denoise CGM Sensor Data. IEEE Trans Biomed Eng 2010: 57(3):634-41.
13. Gonzalo R. Arce, Nonlinear Signal Processing; A Statistical Approach, John Wiley & Sons, Inc., New Jersey, 2005.
14. Gao S, Mateer T. Additive Fast Fourier Transforms Over Finite Fields. IEEE Transactions on Information Theory 2010; 56(12):6265-72.
15. Lauralee Sherwood. Fundamentals of Physiology: A Human Perspective, Thomson Brooks and Cole Inc.,2006.
16. Soni RK, Jain A, Saxena R. An improved and simplified design of Pseudo-transmultiplexer using Blackman window family. Digital Signal Processing 2010;20(3):743-9.
17. John L. Semmlow, Biosignal and Biomedical Image Processing, Marcel Dekker Inc., 2004.
18. Alan V. Oppenhein, Ronald W. Schafer, Discrete-Time Signal Processing, Prentice Hall Signal Processing Series,3rd Ed., 2010.
19. Hsu HW, Liu CM. Autoregressive Modeling of Temporal/Spectral Envelopes with Finite-Length Discrete Trigonometric Transforms. IEEE Transactions on Signal Processing 2010; 58(7):3692-705.
20. Takalo RH, Ihalainen HH. Tutorial on Univariate Autoregressive Spectral Analysis Export. J Clin Monit Comput 2006; 20:379-88.
21. Tracey Cassar, Kenneth P. Camilleri, Simon G. Fabri, Order Estimation of Multivariate ARMA Models. IEEE journal of Selected Topics in Signal Processing 2010;4(3):494-503.
22. K J Blinowska, J Zygierewicz, Practical Biomedical Signal Analysis, Poland, CRC Press (Taylor & Francis Group, LLC), 2011.
23. Fang-Xiang Wu, Wen-Jun Zhang, Dynamic-Model-Based Method for Selecting Significantly Expressed Genes From Time-Course Expression Profiles. IEEE Trans Inform Technol Biomed 2010; 14(1):16-22.
24. Temko A, Lightbody G, Thomas EM, Boylan GB, Marnane W. Instantaneous Measure of EEG Channel Importance for Improved Patient-Adaptive Neonatal Seizure Detection. IEEE Trans Biomed Eng 2012;59(3):717-27.
25. Ramachandran P, Lu WS, Antoniou A. Filter-Based Methodology for the Location of Hot Spots in Proteins and Exons in DNA. IEEE Biomed Eng 2012; 59(6):1598-1609.
26. Acharya UR, Dua S, Du X, Sree S V, Chua CK.Automatic Diagnosis of Glaucoma Using Texture and Higher Order Spectra Features. IEEE Trans Inf Technol Biomed 2011; 15(3):449-55.
27. M. D. Buhmann, Radial Basis Functions: Theory and Implementations, Cambridge University Press, Cambridge, 2004.
28. Tiantian Xie, Hao Yu, Joel Hewlett, Pawel Rozycki, Bogdan Wilamowski. Fast and Efficient Second-order Method for Training Radial Basis Function Networks. IEEE Transactions on Neural Networks and Learning Systems 2012; 23(4):609-19.
Files | ||
Issue | Vol 12, No 3 (2013) | |
Section | Articles | |
Keywords | ||
Asthma Heme oxygenase-1 Mesenchymal stromal cells T-Lymphocytes Regulatory |
Rights and permissions | |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |