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Updated: Aug 20, 2026
Visualization of Vascular and Parenchymal Regeneration after 70% Partial Hepatectomy in Normal Mice
Published on: September 13, 2016
Using higher-order crossings to distinguish liver regeneration indices in hepatectomized diabetic and non-diabetic
Christos Liatsos1, Leontios J Hadjileontiadis, Stamos Theocharis
1Department of Experimental Pharmacology, Medical School, University of Athens, Athens, Greece.
Background And Aims:
Diabetes mellitus is implicated in several liver diseases; hence, its potential affection to liver regenerative capacity is an open research question. So far, only sporadic studies have addressed this issue, mainly using basic statistical techniques. The current study evaluated the ability of a novel technique, namely higher-order crossings (HOC), based on liver DNA biosynthesis and thymidine kinase (TK) enzymatic activity data, to discriminate liver regeneration processes between hepatectomized diabetic and non-diabetic rats.
Methods:
We used 251 adult male rats, divided in two groups; diabetic by Alloxan injection and non-diabetic control, subjected to 70% partial hepatectomy and killed at different time intervals post-partial hepatectomy (PH) (0-240 h). The rate of tritiated thymidine (3HTdR) incorporation into hepatic DNA and the enzymatic activity of liver TK were estimated and, after proper interpolation, were analyzed using HOC sequences. Changes of the latter were captured and used as a means for linear discrimination between the two groups.
Results:
Ninth-order HOC estimated for post-PH (24, 28, 40, 44, 72 and 84 h) exhibited linear discrimination for the rate of 3HTdR incorporation, whereas second-order HOC estimated for (44-72 h) post-PH exhibited linear discrimination for the TK enzymatic activity data. Fuzzy logic-based c-means cluster analysis of HOC provided distinct areas of group categorization (100% accuracy) for diagnostic distinctions (P < 0.001). The data grouping pointed out by the HOC-based analysis revealed an onset delay in the liver regeneration process when Alloxan diabetes was present (P < 0.05).
Conclusions:
Our results suggest that HOC have the potential to linearly discriminate between experimentally induced diabetic and non-diabetic liver regeneration post-PH processes, based on two liver regeneration indices, capturing the delay seen in the liver regeneration process due to Alloxan diabetes, fostering their use as an efficient classification tool. In this way, HOC could be used as an advanced, easily implemented and user-friendly method to thoroughly analyze liver regeneration processes.
