SIMET - Spectral Impedance Measurements of Epithelial Tissue
Year: 2026
Type: dataset
Abstract: The SIMET dataset consists of experimental impedance spectra of epithelial cell monolayers, recorded in an Ussing chamber by impedance spectroscopy [1]. Measurements were performed on the three epithelial cell lines `HT29/B6`, `IPEC-J2`, and `MDCK I`. For each cell line, spectra were acquired under physiological control conditions and after application of EGTA, Nystatin, and their combination (EGTA+Nystatin). EGTA chelates extracellular calcium and thereby opens the paracellular tight junctions, whereas Nystatin permeabilizes the apical cell membrane and thus reduces the transcellular resistance; the combination perturbs the paracellular and transcellular pathways simultaneously. For each sample, a spectral impedance measurement was recorded for 42 frequencies between 1.3 Hz and 16.35 kHz, stored as the real and imaginary part of the complex impedance. A synthetic counterpart of this dataset, in which the same cell lines and conditions are modeled from estimated tissue properties, is available at [3] and described in [4]. For more information on the measurement principle see [1,2]. Important: You are cordially invited to use this dataset (and its synthetic counterpart [3]) for your research or teaching purposes. For example, to compare your impedance analysis approach with ours. If you use this dataset for a scientific publication, please cite this record. If you have any questions or remarks, please do not hesitate to contact me via email (benjamin.schindler at medizin.uni-halle.de). Number of spectra Cell line Control EGTA Nystatin EGTA+Nystatin Total HT29/B6 171 9 30 10 220 IPEC-J2 42 6 72 16 136 MDCK I 115 120 135 — 370 Total 328 135 237 26 726 For `MDCK I`, no EGTA+Nystatin measurements are available. Changelog Version 1.0 -> initial upload References [1] D. Günzel, S. S. Zakrzewski, T. Schmid, M. Pangalos, J. Wiedenhoeft, C. Blasse, C. Ozboda, and S. M. Krug, “From TER to trans- and paracellular resistance: lessons from impedance spectroscopy,” *Annals of the New York Academy of Sciences* 1257(1), pp. 142–151, 2012. [2] T. Schmid, “Automatisierte Analyse von Impedanzspektren mittels konstruktivistischen maschinellen Lernens,” Ph.D. dissertation, Universität Leipzig, Germany, 2018. [3] Schindler, B., Günzel, D., & Schmid, T. (2026). Synthesized Impedance Spectra Measurements of Epithelial Tissue [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.5718938 [4] B. Schindler, D. Günzel, and T. Schmid, “Transcending Two-Path Impedance Spectroscopy with Machine Learning: A Computational Study on Modeling and Quantifying Electric Bipolarity of Epithelia,” International Journal On Advances in Life Sciences 13(1-2), 2021.
Language: English
Subfield: Neurology
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7225759810