Hostname: page-component-848d4c4894-4hhp2 Total loading time: 0 Render date: 2024-06-10T13:18:04.570Z Has data issue: false hasContentIssue false
  • English
  • Français

Gray-Level Co-Occurrence Matrix Analysis of Granule Neurons of the Hippocampal Dentate Gyrus Following Cortical Injury

Published online by Cambridge University Press:  17 January 2020

Igor Pantic ,
Rada Jeremic ,
Sanja Dacic ,
Sanja Pekovic ,
Senka Pantic ,
Marina Djelic ,
Zagorka Vitic ,
Predrag Brkic  and
Claude Brodski
Igor Pantic
Affiliation:
Faculty of Medicine, Institute of Medical Physiology, University of Belgrade, Visegradska 26/II, RS-11129Belgrade, Serbia University of Haifa, 199 Abba Hushi Blvd., Mount Carmel, Haifa, IL-3498838, Israel
Rada Jeremic
Affiliation:
Faculty of Medicine, Institute of Medical Physiology, University of Belgrade, Visegradska 26/II, RS-11129Belgrade, Serbia
Sanja Dacic
Affiliation:
Department for General Physiology and Biophysics, Institute of Physiology and Biochemistry “Ivan Djaja”, Faculty of Biology, University of Belgrade, Studentski trg 16, 11000Belgrade, Serbia
Sanja Pekovic
Affiliation:
Department of Neurobiology, Institute for Biological Research “Sinisa Stankovic”- National Institute of Republic of Serbia, University of Belgrade, Blvd despota Stefana 142, Belgrade, Serbia
Senka Pantic
Affiliation:
School of Medicine, Institute of Histology and Embryology, University of Belgrade, Visegradska 26/II, RS-11129Belgrade, Serbia
Marina Djelic
Affiliation:
Faculty of Medicine, Institute of Medical Physiology, University of Belgrade, Visegradska 26/II, RS-11129Belgrade, Serbia
Zagorka Vitic
Affiliation:
Department of Physiology and Cell Biology, Zlotowski Center for Neuroscience, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beersheba, Israel
Predrag Brkic
Affiliation:
Faculty of Medicine, Institute of Medical Physiology, University of Belgrade, Visegradska 26/II, RS-11129Belgrade, Serbia
Claude Brodski*
Affiliation:
Department of Physiology and Cell Biology, Zlotowski Center for Neuroscience, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beersheba, Israel
*
*Author for correspondence: Claude Brodski, E-mail: claude@bgu.ac.il
Get access

Abstract

Traumatic brain injury (TBI) is a main cause of death and disabilities in young adults. Although learning and memory impairments are a major clinical manifestation of TBI, the consequences of TBI on the hippocampus are still not well understood. In particular, how lesions to the sensorimotor cortex damage the hippocampus, to which it is not directly connected, is still elusive. Here, we study the effects of sensorimotor cortex ablation (SCA) on the hippocampal dentate gyrus, by applying a highly sensitive gray-level co-occurrence matrix (GLCM) analysis. Using GLCM analysis of granule neurons, we discovered, in our TBI paradigm, subtle changes in granule cell (GC) morphology, including textual uniformity, contrast, and variance, which is not detected by conventional microscopy. We conclude that sensorimotor cortex trauma leads to specific changes in the hippocampus that advance our understanding of the cellular underpinnings of cognitive impairments in TBI. Moreover, we identified GLCM analysis as a highly sensitive method to detect subtle changes in the GC layers that is expected to significantly improve further studies investigating the impact of TBI on hippocampal neuropathology.

Keywords

dentate gyrusgray-level co-occurrence matrix analysishippocampussensorimotor cortex ablationtexturetraumatic brain injury
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 26 , Issue 1 , February 2020 , pp. 166 - 172
Copyright
Copyright © Microscopy Society of America 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

a

These authors contributed equally to this work.

References

Amaral, DG, Scharfman, HE & Lavenex, P (2007). The dentate gyrus: Fundamental neuroanatomical organization (dentate gyrus for dummies). Prog Brain Res 163, 3–22.CrossRefGoogle Scholar
Arasi, PRE & Suganthi, M (2019). A clinical support system for brain tumor classification using soft computing techniques. J Med Syst 43, 144.CrossRefGoogle ScholarPubMed
Bilang-Bleuel, A, Ulbricht, S, Chandramohan, Y, De Carli, S, Droste, SK & Reul, JM (2005). Psychological stress increases histone H3 phosphorylation in adult dentate gyrus granule neurons: Involvement in a glucocorticoid receptor-dependent behavioural response. Eur J Neurosci 22, 1691–1700.CrossRefGoogle Scholar
Brianezi, G, Handel, AC, Schmitt, JV, Miot, LD & Miot, HA (2015). Changes in nuclear morphology and chromatin texture of basal keratinocytes in melasma. J Eur Acad Dermatol Venereol 29, 809–812.CrossRefGoogle ScholarPubMed
Brkic, P, Stojiljkovic, M, Jovanovic, T, Dacic, S, Lavrnja, I, Savic, D, Parabucki, A, Bjelobaba, I, Rakic, L & Pekovic, S (2012). Hyperbaric oxygenation improves locomotor ability by enhancing neuroplastic responses after cortical ablation in rats. Brain Inj 26, 1273–1284.CrossRefGoogle ScholarPubMed
Bustamante, C, Bilbao, P, Contreras, W, Martinez, M, Mendoza, A, Reyes, A & Pascual, R (2010). Effects of prenatal stress and exercise on dentate granule cells maturation and spatial memory in adolescent mice. Int J Dev Neurosci 28, 605–609.CrossRefGoogle ScholarPubMed
Carpenter, AE, Jones, TR, Lamprecht, MR, Clarke, C, Kang, IH, Friman, O, Guertin, DA, Chang, JH, Lindquist, RA, Moffat, J, Golland, P & Sabatini, DM (2006). CellProfiler: Image analysis software for identifying and quantifying cell phenotypes. Genome Biol 7: R100.CrossRefGoogle ScholarPubMed
Chaddad, A, Desrosiers, C, Bouridane, A, Toews, M, Hassan, L & Tanougast, C (2016). Multi texture analysis of colorectal cancer continuum using multispectral imagery. PLoS One 11, e0149893.CrossRefGoogle ScholarPubMed
Chandramohan, Y, Droste, SK & Reul, JM (2007). Novelty stress induces phospho-acetylation of histone H3 in rat dentate gyrus granule neurons through coincident signalling via the N-methyl-D-aspartate receptor and the glucocorticoid receptor: Relevance for c-fos induction. J Neurochem 101, 815–828.CrossRefGoogle ScholarPubMed
Chen, X, Wei, X, Zhang, Z, Yang, R, Zhu, Y & Jiang, X (2015). Differentiation of true-progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide by GLCM texture analysis of conventional MRI. Clin Imaging 39, 775–780.CrossRefGoogle ScholarPubMed
De Mello, MR, Albuquerque, DM, Pereira-Cunha, FG, Albanez, KB, Pagnano, KB, Costa, FF, Metze, K & Lorand-Metze, I (2012). Molecular characteristics and chromatin texture features in acute promyelocytic leukemia. Diagn Pathol 7: 75.CrossRefGoogle ScholarPubMed
Di Ieva, A (2016). The Fractal Geometry of the Brain. New York: Springer Nature (Springer Series in Computational Neuroscience).CrossRefGoogle Scholar
Fa, M, Xia, L, Anunu, R, Kehat, O, Kriebel, M, Volkmer, H & Richter-Levin, G (2014). Stress modulation of hippocampal activity–spotlight on the dentate gyrus. Neurobiol Learn Mem 112, 53–60.CrossRefGoogle ScholarPubMed
Fumagalli, S, Fiordaliso, F, Perego, C, Corbelli, A, Mariani, A, De Paola, M & De Simoni, MG (2009). The phagocytic state of brain myeloid cells after ischemia revealed by superresolution structured illumination microscopy. J Neuroinflammation 16, 9. doi:10.1186/s12974-019-1401-z.CrossRefGoogle Scholar
Haralick, RSK & Dinstein, I (1973). Textural features for image classification. IEEE Trans Syst Man Cybern 3, 610–621.CrossRefGoogle Scholar
Kamentsky, L, Jones, TR, Fraser, A, Bray, MA, Logan, DJ, Madden, KL, Ljosa, V, Rueden, C, Eliceiri, KW & Carpenter, AE (2011). Improved structure, function and compatibility for CellProfiler: Modular high-throughput image analysis software. Bioinformatics 27, 1179–1180.CrossRefGoogle ScholarPubMed
Kleppe, M, et al. (2018). Dual targeting of oncogenic activation and inflammatory signaling increases therapeutic efficacy in myeloproliferative neoplasms. Cancer Cell 33, 785–787.CrossRefGoogle ScholarPubMed
Kolarević, D, Vujasinović, T, Kanjer, K, Milovanović, J, Todorović-Raković, N, Nikolić-Vukosavljević, D & Radulovic, M (2018). Effects of different preprocessing algorithms on the prognostic value of breast tumour microscopic images. J Microsc 270, 17–26.CrossRefGoogle ScholarPubMed
Kuliffay, P, Sanislo, L & Galbavy, S (2010). Chromatin texture, DNA index, and S-phase fraction in primary breast carcinoma cells analysed by laserscanning cytometry. Bratisl Lek Listy 111, 4–8.Google ScholarPubMed
Lamprecht, MR, Sabatini, DM & Carpenter, AE (2007). CellProfiler: Free, versatile software for automated biological image analysis. BioTechniques 42, 71–75.CrossRefGoogle ScholarPubMed
Lee, J, Jain, R, Khalil, K, Griffith, B, Bosca, R, Rao, G & Rao, A (2015). Texture feature ratios from relative CBV maps of perfusion MRI are associated with patient survival in glioblastoma. AJNR Am J Neuroradiol 37, 37–43.CrossRefGoogle ScholarPubMed
Mapayi, T, Viriri, S & Tapamo, JR (2015). Adaptive thresholding technique for retinal vessel segmentation based on GLCM-energy information. Comput Math Methods Med 2015, 597475.Google ScholarPubMed
Pantic, I, Dacic, S, Brkic, P, Lavrnja, I, Jovanovic, T, Pantic, S & Pekovic, S (2015). Discriminatory ability of fractal and grey level co-occurrence matrix methods in structural analysis of hippocampus layers. J Theor Biol 370, 151–156.CrossRefGoogle ScholarPubMed
Pantic, I, Dacic, S, Brkic, P, Lavrnja, I, Pantic, S, Jovanovic, T & Pekovic, S (2014). Application of fractal and grey level co-occurrence matrix analysis in evaluation of brain corpus callosum and cingulum architecture. Microsc Microanal 20, 1373–1381.CrossRefGoogle ScholarPubMed
Pantic, I, Dimitrijevic, D, Nesic, D & Petrovic, D (2016 b). Gray level co-occurrence matrix algorithm as pattern recognition biosensor for oxidopamine-induced changes in lymphocyte chromatin architecture. J Theor Biol 406, 124–8.CrossRefGoogle ScholarPubMed
Pantic, I, Nesic, Z, Paunovic Pantic, J, Radojevic-Skodric, S, Cetkovic, M & Basta Jovanovic, G (2016 a). Fractal analysis and gray level co-occurrence matrix method for evaluation of reperfusion injury in kidney medulla. J Theor Biol 397, 61–67.CrossRefGoogle ScholarPubMed
Pantic, I, Pantic, S, Paunovic, J & Perovic, M (2013). Nuclear entropy, angular second moment, variance and texture correlation of thymus cortical and medullar lymphocytes: Grey level co-occurrence matrix analysis. An Acad Bras Cienc 85, 1063–1072.CrossRefGoogle ScholarPubMed
Paxinos, G & Watson, C (2004). The Rat Brain in Stereotaxic Coordinates - The New Coronal Set, 5th ed. New York, NY: Academic Press.Google Scholar
Qin, Y, Karst, H & Joels, M (2004). Chronic unpredictable stress alters gene expression in rat single dentate granule cells. J Neurochem 89, 364–374.CrossRefGoogle ScholarPubMed
Schoenfeld, TJ & Gould, E (2012). Stress, stress hormones, and adult neurogenesis. Exp Neurol 233, 12–21.CrossRefGoogle ScholarPubMed
Shamir, L, Wolkow, CA & Goldberg, IG (2009). Quantitative measurement of aging using image texture entropy. Bioinformatics 25, 3060–3063.CrossRefGoogle ScholarPubMed
Song, CI, Ryu, CH, Choi, SH, Roh, JL, Nam, SY & Kim, SY (2013). Quantitative evaluation of vocal-fold mucosal irregularities using GLCM-based texture analysis. Laryngoscope 123, E45–E50.CrossRefGoogle ScholarPubMed
Tan, TC, Ritter, LJ, Whitty, A, Fernandez, RC, Moran, LJ, Robertson, SA, Thompson, JG & Brown, HM (2016). Gray level co-occurrence matrices (GLCM) to assess microstructural and textural changes in pre-implantation embryos. Mol Reprod Dev 83, 701–713.CrossRefGoogle ScholarPubMed
Veskovic, M, Labudovic-Borovic, M, Zaletel, I, Rakocevic, J, Mladenovic, D, Jorgacevic, B, Vucevic, D & Radosavljevic, T (2018). The effects of betaine on the nuclear fractal dimension, chromatin texture, and proliferative activity in hepatocytes in mouse model of nonalcoholic fatty liver disease. Microsc Microanal 24, 132–138.CrossRefGoogle ScholarPubMed
Yang, X, Tridandapani, S, Beitler, JJ, Yu, DS, Yoshida, EJ, Curran, WJ & Liu, T (2012). Ultrasound GLCM texture analysis of radiation-induced parotid-gland injury in head-and-neck cancer radiotherapy: An in vivo study of late toxicity. Med Phys 39, 5732–5739.CrossRefGoogle Scholar
Zhu, H, Jiang, H, Li, S, Li, H & Pei, Y (2019). A novel multispace image reconstruction method for pathological image classification based on structural information. Biomed Res Int 2019, 3530903. doi:10.1155/2019/3530903.CrossRefGoogle ScholarPubMed