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SSN 2410-7751 (Print)
ISSN 2410-776X (Online)
"Biotechnologia Acta" V. 10, No 3, 2017
https://doi.org/10.15407/biotech10.03.031
Р. 31-40, Bibliography 21, English
Universal Decimal Classification: 004:591.5:612:616-006
ON THE MATHEMATICAL METHODS IN BIOLOGY AND MEDICINE
Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology of the National Academy of Sciences of Ukraine, Kyiv
The aim of the work was to analyze the range of mathematical methods and to choose the most prospective ones from the point of view of application in biology and medicine. After analyzing of approximately 200 current publications, a list of respective methods was completed. This list includes both the most recent, intensively developed methods as well as traditionally used ones — mathematical statistics, stochastic methods, regression analysis, and others. From the first group the methods of cluster analysis, artificial neural networks and image processing were subdivided. A description of each of these methods and examples of their application in practice are given. A separate group is dedicated to complex modern works, in which the problems requiring the complex application of several methods are present. In conclusions a brief assessment of the methods of cluster analysis, artificial neural networks, image processing methods are given as well as recommendations for their practical application.
Key words: processing, data bases.
© Palladin Institute of Biochemistry of National Academy of Sciences of Ukraine, 2017
References
1. Klyuchko O. M. Information and computer technologies in biology and medicine. Kyiv: NAU-druk. 2008. 252 p. (In Ukrainian).
2. Kondrashov S. N, Gorokhova M. N. Develop ment of an algorithm for optimal control of the process of formaldehyde production. Vestnik PNIPU “Chemical technology and biotechnology”. 2016, No. 1, P. 718. (In Russian).
3. “Classification and search of biomarkers in proteomics”. Available at http://bioinformatics.ru/Raznoe/Klassifikatciia-i-poiskbiomarkerov-v-proteomike.html (In Russian).
4. D’haeseleer P. How does gene expression clustering work? Nature Biotechnology. 2005, No. 23, 1499–1501. https://doi.org/10.1038/nbt1205-1499
5. Karpov P. A., Nadezhdina E. S., Emets A. I, Blum Y. B. Cluster analysis of similarity of microtubule-associated and cell cycle of human serine-threonine protein kinases with their plant homologues. Bulletin of the Moscow University. Series 16: Biology. Moscow. 2010, No 4. (In Russian).
6. Iakovidis D. K., Maroulis D. E., Karkanis S. A. Texture multichannel measurements for cancer precursors’ identification using support vector machines. Measurement. 2004, V. 36, P. 297313. https://doi.org/10.1016/j.measurement.2004.09.010
7. Brenton J. D. Carey L. A., Ahmed A. A. Molecular classification and molecular forecasting of breast cancer: ready for clinical application? J. Clin. Oncol. 2005, 23 (29), 7350–7360. https://doi.org/10.1200/JCO.2005.03.3845
8. Bozhenko V. K. Multivariable analysis of laboratory blood parameters for obtaining diagnostic information in experimental and clinical oncology. The dissertation author’s abstract on scientific degree editions. Dc. med. study. Moscow, 2004. (In Russian).
9. Tashkinov A. A, Wildeman A. V, Bronnikov V. A. Application of the classification tree method to predict the level of development of motility in patients with impaired motor functions. Russian Journal of Biomechanics. 2008, 12 (4), 8495. (In Russian).
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11. Goldys E. M. Fluorescence Applications in Biotechnology and the Life Sciences. USA: John Wiley & Sons. 2009, 367 p.
12. Perner P., Salvetti O. Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry. Proceedings of the third International Conference, Leipzig, (Germany): Springer. 2008, 173 p. https://doi.org/10.1007/978-3-540-70715-8
13. Gavrilovich M. Spectraimage processing and application in biotechnology and pathology. Dissertation for Ph.D. Acta Universitatis Upsaliensis. Upsala. 2011, 63 p.
14. Shutko V. M, Shutko O. M., Kolganova O. O. Methods and means of compression of information. Kyiv: NAU-druk, 2012, 168 p. (In Ukrainian).
15. Natrajan R., Sailem H., Mardakheh F. K., Garcia M. F., Tape C. J., Dowsett M., Bakal C., YuanY. Micro environmental heterogeneity parallels breast cancer progression: a histology–genomic integration analysis. PLoS medicine. 2016, 13 (2), e1001961. https://doi.org/10.1371/journal. pmed.1001961.
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17. Moghaddam M. G., Ahmad F. B. H., Basri M., Rahman M. B. A. Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester. Electronic Journal of Biotechnology. 2010, 13 (3), 915. https://doi.org/10.2225/vol13-issue3-fulltext-9
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19. Kallan G. Basic Concepts of Neural Networks. Moscow: Williams. 2001. 268 p. (In Russian).
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21. Onopchuk Yu. M., Biloshitsky P. V., Klyuchko O. M. Development of mathematical models based on the results of researches of Ukrainian scientists at Elbrus. Visnyk NAU, 2008, No. 3, P. 146155. (In Ukrainian).
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ISSN 2410-776X (on-line)
"Biotechnologia Acta" V. 10, No 3, 2017
https://doi.org/10.15407/biotech10.03.065
Р. 65-71, Bibliography 10, English
Universal Decimal Classification: 631.46.631.445.41:631.84
National Scientific Center “Institute of Agriculture of the National Academy of Agrarian Sciences of Ukraine”, Chabany, Ukraine
The aim of the work was to determine the possibility of using the number and activity of Azotobacter cells and melanin-synthesizing micromycetes as indicators of gray forest soils of different types (fallow, extensive and intensive agrosoil) pollution with heavy metal ions. For this purpose, there were used laboratory-analytical, microbiological and statistical methods. As a result of research of increasing doses of heavy metals (zinc + lead) influence on the number of microorganisms in the gray forest soils it was found that the number and activity of Azotobacter and the number and part of melanin-synthesizing micromycetes in their total number may be fit into indicators of pollution with heavy metals. Azotobacter cells activity index may be considered indicative at contamination levels of 5-100 of maximum permissible concentrati{spoiler title=Скрытый текст}{/spoiler}on in the absence of vegetation, at contamination levels of 10–100 – for soils with phytocenosis. The number and proportion of melaninsynthesizing micromycetes in total guantity may serve as diagnostic sign of gray forest soils pollution with high doses of heavy metals, but only for the period of contamination up to 2 years.
It was shown that nature of the effect of heavy metals on the number of microorganisms of indicative groups depended on the presence of plants in the monitoring system, on doses of heavy metals, on the term of contamination and on the type of soil usage.
Key words: Azotobacter, melanin-synthesizing micromycetes, diagnostic indicator, pollution, heavy metals.
© Palladin Institute of Biochemistry of National Academy of Sciences of Ukraine, 2017
References
1. Bernard L., Maron Р., Mougel С., Nowak V., L?v?que J., Marol C., Balesdent J., Gibiat J., Ranjard L. Contamination of soil by copper affects the dynamics, diversity, and activity of soil bacterial communities involved in wheat decomposition and carbon storage. Appl. Environ. Microbiol. 2009, 75 (23), 7565–7569.
2. Anderson J., Hooper М., Zak J., Cox S. Characterization of the structural and functional diversity of indigenous soil microbial communities in smelter-impacted and nonimpacted soils. Environ. Toxicol. Chem. 2009, 28 (3), 534–541.
3. Mosina L. V. Features of microbial components functioning in a soil-plant system in conditions of high soil contamination with heavy metals and unregulated recreation. Proc. TSKhA. 2010, N 282, P. 732–739. (In Russian).
4. Malinovska I. M., Dombrovska I. V. State of microbiota gray forest soils under different using. Visnyk Kyivskoho Natsionalnoho Universytetu. Ser. Biol. 2011, Issue 57, P. 21–25. (In Ukrainian).
5. Selivanovskaya S. Yu., Kiyamova S. N., Latypova V. Z., Alimova F. K. Effect of sedimentary waste water containing metals on microbial cenosis of wood gray soil. Pochvovedeniye. 2001, N 5, P. 588–594. (In Russian).
6. Malinovska I. M., Zinoviev N. A. The direction and intensity of microbiological processes in dark gray ashed soils contaminated with petroleum. Visnyk Poltavskoi derzhavnoi ahrarnoi akademii. 2010, N 4, P. 17–23. (In Ukrainian).
7. Kolosvary I. Data concerning the possibility of using the abundance of the Azotobacter cells as bioindicator of soil pollution. Stud. Univ. Babes-Bolyai. Biol. 1998, N 1–2, P. 137–141.
8. Kozhevin P. A., Kozhevina L. S., Bolotina I. N. Definition of bacteria state in ground. Doklady AN SSSR. 1987, 297 (5), 1247–1249. (In Russian).
9. Bernlohr R. W., Webster G. C. Effect of chloramphenicol on protein and nucleic acid metabolism in Azotobacter agilis. J. Bacteriol. 1958, 76 (3), 233–238.
9. Khovrychev M. P., Semenova A. M., Rabotnova I. L. The action of zinc ions on Candida utilis. Mikrobiol. 1980, T. XIX, V. 1, P. 59–63. (In Russian).
10. Zhdanova N. N., Wasilewskaia A. N. Mushrooms containing melanin in extreme conditions. Kyiv: Naukova dumka. 1988, 196 p. (In Ukranian).
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SSN 2410-7751 (Print)
ISSN 2410-776X (Online)
"Biotechnologia Acta" V. 10, No 3, 2017
https://doi.org/10.15407/biotech10.03.057
Р. 57-64, Bibliography 36, English
Universal Decimal Classification: 576.311.34:582.661.15
CHLOROPLASTS ULTRASTRUCTURAL CHANGES AS BIOMARKERS OF ACID RAIN AND HEAVY METALS POLLUTION
Kholodny Institute of Botany of the National Academy of Sciences of Ukraine, Kyiv
The aim of the work was to confirm the possibility of structural changes of Spinacea olearacea L. chloroplasts usage as biomarkers for assessing of environmental pollution by acid rain and heavy metals. Chloroplasts ultrastructural changes were recorded by transmission electron microscopy. Data on changes in the structure of chloroplasts under the influence of these factors are obtained, in particular the heterogeneity of thylakoid grana packing, the membranes thickness, the starch grains presence, and the lumen space increase as compared with the control. These structural changes can be applied as markers of abiotic stresses influence, notably acid rain and heavy metals, and for the creation of new sustainable high-tech varieties of agricultural crops.
Key words: Spinacea olearacea L., imitated acid rains, heavy metals, chloroplast structure, biomarkers..
© Palladin Institute of Biochemistry of National Academy of Sciences of Ukraine, 2017
References
1. Bazhin N. M. Acid rain. Soros Educational J. 2001, 7 (7), 47–52. (In Russian).
2. Seinfield J. H. Atmospheric Chemistry and Physics from Air Pollution to Climate Damage. AVI publishing Co, West Print Connecticut. 1998, P. 224.
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4. Ivanov A. F. The growth of woody plants and soil acidity. Minsk: Science and technology. 1970, P. 216. (In Russian).
5. Neufeld H. S. Direct foliar effects of simulated acid rain. Damage, growth and gas exchange. New Phytol. 1985, V. 99, P. 389–405. https://doi.org/10.1111/j.1469-8137.1985.tb03667.x
6. Velikova V. Light and CO2 responses of photosynthesis and chlorophyll fluorescence characteristics in bean plants after simulated acid rain. Physiol. Plant. 1999, V. 107, P. 77–83. https://doi.org/10.1034/j.1399-3054.1999.100111.x
7. Qiu D. Effects of simulated acid rain on chloroplast activity in Dimorcarpus longana Lour. cv. wulongling leaves. Ying Yong Sheng Tai Xue Bao. 2002, V. 12, P. 1559–1562.
8. Hogan G. D. Effects of acid deposition on hybrid poplar-primary or predisposing stress. Water Air Soil Pollut. 1995, V. 85, P. 1419–1424. https://doi.org/10.1007/BF00477180
9. Shan Y. The individual and combined effects of ozone and simulated acid rain on chlorophyll content, carbon allocation and biomass accumulation of armand pine seedlings. Water Air Soil Pollut. 1995, V. 85, P. 1399–1404. https://doi.org/10.1007/BF00477177
10. Gabara B. Changes in the ultrastructure of chloroplasts and mitochondria and antioxidant enzyme activity in Lycopersicon esculentum Mill. leaves sprayed with acid rain. Plant Sci. 2003, V. 164, P. 507–516. https://doi.org/10.1016/S0168-9452(02)00447-8
11. Stoyanova D. Effects of simulated acid rain on chloroplast ultrastructure of primary leaves of Phaseolus vulgaris. Biol. Plant. 1997, V. 40, P. 589–595. https://doi.org/10.1023/A:1001761421851
12. Tarhanen S. Ultrastructural responses of the lichen Bryoria fuscesens to simulated acid rain and heavy metal deposition. Ann. Bot. 1998, V. 82, P. 735–746. https://doi.org/10.1006/anbo.1998.0734
13. Ivanchenko V. M. Photosynthesis and the structural state of the chloroplast. Minsk: Science and technology. 1974, P. 160. (In Russian).
14. Shabelskaya E. F., Gvardiyan V. N. Status of the photosynthetic apparatus of higher green plants in full shade. Minsk: Nauka. 1971, P. 132–138. (In Russian).
15. Stroganov B. P. Kabanov N. I. Structure and function of cells under salinity. Moskwa: Nauka. 1970, P. 318. (In Russian).
16. Wrischer M. Elektronenmikroskopische Untersuchungen der Zellnekrobiose. Protoplasma. 1965, V. 60, Р. 355–400.
17. Vodka M. V., Bilyavs'ka N. O. Chloroplast structural and functional changes as biomarkers. Biotechnol. acta. 2016, 9 (1), 103–107.
18. Rokitsky P. F. Biological Statistics. Minsk: Vysheyshaya School. 1973, P. 320. (In Russian).
19. Kratsch H. A., Wise R. R. The ultrastructure of chilling stress. Plant, Cell, Environm. 2000. 23 (4), 337–350. https://doi.org/10.1046/j.1365-3040.2000.00560.x
20. Gamaley Y. Phloem of leaf: Development of the structure and functions in connection with the evolution of flowering plants. Leningrad: Science. 1990, P. 144. (In Russian).
21. Peng H. Accumulation andultrastructural distribution of copper in Elsholtzia splendens. J. Zhejiang Univ. Sci. 2005, V. 6, Р. 311–318.
22. Hakmaoui A. Copper and cadmium tolerance, uptake and effect on chloroplast ultrastructure. Studies on Salix purpurea and Phragmites australis. Zh. Naturforschung. 2007, 62 (5–6), 417–426. https://doi.org/10.1515/znc-2007-5-616
23. Jiang H. M. Effects of external phosphorus on the cell ultrastructure and the chlorophyll content of maize under cadmium and zinc stress. Environm. Pollut. 2007, 147 (3), 750–756. https://doi.org/10.1016/j.envpol.2006.09.006
24. Bernal M. Excess copper effect on growth, chloroplast ultrastructure, oxygen-evolution activity and chlorophyll fluorescence in Glycine max cell suspensions. Physiologia Plantarum. 2006, 127 (2), 312–325. https://doi.org/10.1111/j.1399-3054.2006.00641.x
25. Doncheva S. Influence of succinate on zinc toxicity of pea plants. J. Plant nutrition. 2001, 24 (6), 789–804. https://doi.org/10.1081/PLN-100103774
26. Panou-Filotheou H. Effects of copper toxicity on leaves of oregano (Origanum vulgare subsp. hirtum). Ann. Bot. 2001, 88 (2), 207–214. https://doi.org/10.1006/anbo.2001.1441
27. Austin J. R. Plastoglobules are lipoprotein subcompartments of the chloroplast that are permanently coupled to thylakoid membranes and contain biosynthetic enzymes. The Plant Cell. 2006, 18 (7), 1693–1703. https://doi.org/10.1105/tpc.105.039859
28. Br?h?lin C. The plastoglobule: a bag full of lipid biochemistry tricks. Photochem. Photobiol. 2008, 84 (6), 1388–1394. https://doi.org/10.1111/j.1751-1097.2008.00459.x
29. Spicher L. Unexpected roles of plastoglobules (plastid lipid droplets) in vitamin K 1 and E metabolism. Curr. Opin. Plant Biol. 2015, V. 25, P. 123–129. https://doi.org/10.1016/j.pbi.2015.05.005
30. Besagni C. A mechanism implicating plastoglobules in thylakoid disassembly during senescence and nitrogen starvation. Planta. 2013, 237 (2), 463–470. https://doi.org/10.1007/s00425-012-1813-9
31. Farmer E. E. ROS-mediated lipid peroxidation and RES-activated signaling. Ann. Rev. Plant Biol. 2013, V. 64, P. 429–450. https://doi.org/10.1146/annurev-arplant-050312-120132
32. Demidchik V. Mechanisms and physiological roles of K+ efflux from root cells. J. Plant Physiol. 2014, 171 (9), 696–707. https://doi.org/10.1016/j.jplph.2014.01.015
33. Lin Q. Subcellular localization of copper in tolerant and non-tolerant plant. J. Environm. Sci. 2005, 17 (3), 452–456.
34. Azzarello E. Ultramorphological and physiological modifications induced by high zinc levels in Paulownia tomentosa. Environm. Exp. Bot. 2012, 81 (1), 11–17. https://doi.org/10.1016/j.envexpbot.2012.02.008
35. Kawachi M. A mutant strain Arabidopsis thaliana that lacks vacuolar membrane zinc transporter MTP1 revealed the latent tolerance to excessive zinc. Plant, Cell Physiol. 2009, 50 (6), 1156–1170. https://doi.org/10.1093/pcp/pcp067
36. Clemens S. Molecular mechanisms of plant metal tolerance and homeostasis. Planta. 2001, 212 (4), 475–486. https://doi.org/10.1007/s004250000458
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SSN 2410-7751 (Print)
ISSN 2410-776X (Online)
"Biotechnologia Acta" V. 10, No 3, 2017
https://doi.org/10.15407/biotech10.03.050
Р. 50-56, Bibliography 13, English
Universal Decimal Classification: 664.15
IGRADIENT-CONTINUOUS YEAST CULTIVATION FOR THE ALCOHOL PRODUCTION FROM MOLASSES
Levandovskiy L. V., Myhailyk V. S.
Kyiv National University of Trade and Economics, Ukraine
This work objective is to find the technological conditions for the intensification of yeast growth in the gradient-continuous yeast cultivation process. Experiments on four sequential yeast chemostats (connected into a battery) demonstrated broad possibilities to influence the metabolic activity of yeast and the alcohol production depending on the content of molasses introduced into the second, third and fourth yeast generators. Adding the molasses according to the 3:2:1 scheme in quantities, which are sufficient to achieve the initial concentration of solids of 26.5 g/100 cm3 to the end of the process resulted in high accumulation of yeast in the medium (up to 99 g/dm3).
It is demonstrated that the highest ratio of economic effect of biomass synthesis from molasses sugars (88 g/100 g) is achieved when molasses is added according to the 1:2:2.5 scheme and the initial solids concentration in the medium is near 12 g/100 cm3.
Key words: yeast, ethanol, molasses.
© Palladin Institute of Biochemistry of National Academy of Sciences of Ukraine, 2017
References
1. Typical technological regulation of production molasses-alcoholic mash and pressed baking yeast: TR Ukr 18.8049 ? 2004. Kyiv: UkrNDIspyrtbioprod: Ministry of Agrarian Policy of Ukraine. 2004, 62 p. (In Ukrainian).
2. Shiyan P. L., Sosnytskiy V. V., Oliynichuk S. T. Innovative technologies of alcohol industry. Theory and practice. Kyiv: Аskaniia. 2009, 424 p. (In Ukrainian).
3. Levandovsky L. V., Bondar M. V. Features of yeast metabolism in their recirculation provided alcohol fermentation of molasses wort. Mikrobiol. zh. 2016, 78 (1), 52–61. (In Ukrainian).
4. Marynchenko V. A., Domaretskyy V. A., Shiyan P. L. Technology of alcohol. Vinnitsa “Podole. 2000”. 2003, 496 p. (In Russian).
5. Pydgorskyy V. S., Iutynska H. O., Pyrog T. P. Intensification technology of microbial synthesis: Monograph. Kyiv: Naukova dumka. 2010, 327 p. (In Ukrainian).
6. Levandovskiy L. V., Mikhailyk V. Two-product obtaining technology based on continuous gradient yeast generation. Biotechnol. acta. 2016, 9 (5), 38–44. https://doi.org/10.15407/biotech9.05.038
7. Levandovsky L. V., Nichik O. V., Yakovenko A. A. Influence of cultivation duration of alcohol yeast on the results of fermentation of molasses wort. Production of alcohol and alcoholic beverages. 2012, No 2, P. 13–15. (In Russian).
8. Levandovsky L. V., Nichik O. V., Semenyuk Yu. V. Influence of the composition of molasses wort on the effectiveness of two-product of alcohol production and baker’s yeast. Production of alcohol and alcoholic beverages. 2012, No 1, P. 11–13. (In Russian).
9. Ghorbani F., Younesi H. The kinetics of ethanol production from cane molasses by Saccharomyces cerevisiae in a batch bioreactor. Energy Sources, Part A: Recovery, Utilization and Environmental Effects. 2013, 35 (11), 1073–1083.
10. Bouallagui, H., Touhami, Y., Hanafi, N., Ghariani, A., Hamdi, M. Performances comparison between three technologies for continuous ethanol production from molasses. Biomass Bioener. 2013, V. 48, Р. 25–32.
11. De Andrade R., C?ndida Rabelo S., Maugeri Filho F., Maciel Filho R., Carvalho da Costa A. Evaluation of the alcoholic fermentation kinetics of enzymatic hydrolysates from sugarcane bagasse (Saccharum officinarum L.). J. Chem. Technology Biotechnol. 2013, 88 (6), 1049–1057.
12. Herrera W. E., Filho R. M. Development of a monitoring hybrid system for bioethanol production. Chem. Engin. Transact. 2013, V. 32, Р. 943–948.
13. Instructions on technochemical and microbiological control of alcohol production/ratified. Hosahropromom USSR 15.01.1986. N.: Agropromizdat. 1986, 400 p. (In Russian).
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SSN 2410-7751 (Print)
ISSN 2410-776X (Online)
"Biotechnologia Acta" V. 10, No 3, 2017
https://doi.org/10.15407/biotech10.03.041
Р. 41-49, Bibliography 24, English
Universal Decimal Classification: 577.112:57.083.3
POLYCLONAL ANTIBODIES AGAINST HUMAN PLASMINOGEN KRINGLE 5
Palladian Institute of Biochemistry of the National Academy of Sciences of Ukraine, Kyiv
The aim of the research was to obtain the polyclonal antibodies against a fragment of human plasminogen kringle 5 and to study their immunochemical properties. The following approaches were used: immunization of rabbits with plasminogen kringle 5, receiving of high-titer immune serum, synthesis of kringle 5-based affinity sorbent for selection of monospecific antibodies, chromatography on synthesized K 5-Sepharose, ELISA immunoblot assay.
The obtained polyclonal antibodies reacted in ELISA with a plasminogen K 5 fragment, and to a much lesser extent with mini-plasminogen, Lys-plasminogen, K 1-3 and K 4 plasminogen fragments, Glu-plasminogen, in descending order. Based on the dissociation constant determination it was found that these antibodies had high affinity to their epitopes within K 5 fragment (3.89·10–10 M), mini-plasminogen (5.46·10–9 М) and Lys-plasminogen (2.54·10–9 М), and insignificant affinity to K1-3, K4 and Glu-plasminogen. These antibodies reacted in immunoblotting assay with an isolated K 5 fragment of human plasminogen, Lys-Pg and mini-Pg, and did not react with K 5 in Glu-Pg and with K 1-3 or K 4 fragments. Thus, the obtained polyclonal antibodies were monospecific and had a high affinity to kringle 5. These antibodies can be used for the development immuno chemical and immunosensory methods for the quantitative determination of angiostatin K 5 in biological materials.
Key words: human plasminogen fragments, kringle 5, polyclonal antibodies, angiostatines.
© Palladin Institute of Biochemistry of National Academy of Sciences of Ukraine, 2017
References
1. V?radi A., Patthy L. Kringle 5 of human plasminogen carries a benzamidine-binding site. Biochem. Biophys. Res. Communic. 1981, 103 (1), 97–102.
2. Vali Z., Patthy L. Location of the Intermediate and High Affinity w-Aminocarboxylic Acidbinding Sites in Human Plasminogen. J. Biol. Chem. 1982, 257 (4), 2104–2110.
3. Thewes T., Constantine K., Byeon I.-J. L., Llinas M. Ligand Interactions with the Kringle 5 Domain of Plasminogen. J. Biol. Chem. 1990, 265 (7), 3906–3915.
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5. Lu H. Kringle 5 causes cell cycle arrest and apoptosis of endothelial cells. Biochem. Biophys. Res. Communic. 1999, V. 258, Р. 668–673.
6. Cao Y., Chen A., An S. S., Ji R. W., Davidson D., Llin?s M. Kringle 5 of plasminogen is a novel inhibitor of endothelial cell growth. J. Biol. Chem. 1997, V. 272, Р. 22924–22928.
7. Davidson D. J., Haskell C., Majest S., Kherzai A. Kringle 5 of Human Plasminogen Induces Apoptosis of Endothelial and Tumor Cells through Surface-Expressed Glucose-Regulated Protein 78. Cancer Res. 2005, 65 (11), 4663–4672.
8. Perri S. R., Nalbantoglu J., Annabi B., Koty Z., Lejeune L., Fran?ois M., Di Falco M. R., B?liveau R., Galipeau J. Plasminogen Kringle 5–Engineered Glioma Cells Block Migration of Tumor-Associated Macrophages and Suppress Tumor Vascularization and Progression. Cancer Res. 2005, 65 (18), 8359–8365.
9. Gao G., Li Y., Gee S., Dudley A., Fant J., Crosson C., Ma J.-X. Down-regulation of Vascular Endothelial Growth Factor and Up-regulation of Pigment Epithelium-derived Factor. A possible mechanism for the anti-angiogenic activity of plasminogen kringle 5. J. Biol. Chem. 2002, 277 (11) 9492–9497.
10. Ma J., Li Ch., Shao Ch., Gao G., Yang X. Decreased K5 receptor expression in the retina, a potential pathogenic mechanism for diabetic retinopathy. Mol. vision. 2012, V. 18, Р. 330–336.
11. Zhang D., Kaufman P. L., Gao G., Saunders R. A., Ma J. X. Intravitreal injection of plasmino gen kringle 5, an endogenous angiogenic inhibitor, arrests retinal neovascularization in rats. Diabetologia. 2001, V. 44, Р. 757–765.
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13. Kapustianenko L. G., Iatsenko T. A., Yusova E. I., Grinenko T. V. Isolation and purification of a kringle 5 from human plasminogen using AH-Sepharose. Biotechnol. acta. 2014, 7 (4), 35–42. https://doi.org/10.15407/biotech7.04.035
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