Neuro-fuzzy method for predicting the viability of stem cells treated at different time-concentration conditions

Technol Health Care. 2017 Dec 4;25(6):1041-1051. doi: 10.3233/THC-170922.

Abstract

Dental stem cells isolated for human dental pulp are an excellent source for regenerative medicine and dentistry. Simulation of clinical scenario is one of the crucial challenges for evaluation of the efficacy of DPSCs in various regenerative therapies. In this study we evaluated the viability of DPSCs after treatment with artificial bacterial lipopolysaccharides (LPS) as the main component responsible for inducing inflammatory response in majority of the inflammatory conditions in clinical scenario. Although a number of studies have previously treated stem cells with LPS from bacteria, however the accuracy level of the outcome was not established. Here we have analyzed the outcome using adaptive neuro-fuzzy inferences system (ANFIS) to predict the viability of human DPSCs after treatment with bacterial LPS.

Keywords: ANFIS; Dental pulp stem cells; lipopolysaccharides; neuro-fuzzy; prediction.

MeSH terms

  • Algorithms
  • Cell Differentiation
  • Cell Proliferation
  • Dental Pulp / physiology*
  • Dose-Response Relationship, Drug
  • Humans
  • Inflammation / physiopathology*
  • Lipopolysaccharides / pharmacology*
  • Models, Biological
  • Neural Networks, Computer*
  • Stem Cells / physiology*
  • Time Factors

Substances

  • Lipopolysaccharides